README.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
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   "source": [
    "# microfiltR\n",
    "# Processing and filtering marker gene datasets\n",
    "\n",
    "Here, we'll walk through some filtering strategies applicable to compositional marker gene studies. We will employ several custom R functions designed to manipulate phyloseq-class datasets that aid in the processing, filtering, and reproducability of marker gene studies. We apply this workflow to a large 16S community dataset generated from three Illumina MiSeq runs, though these strategies should be widely useful to any marker gene and easily scalable to large datasets with thousands of taxa and samples. _For reference, this entire notebook can be run in about 30 seconds on a 13\" 2013 Macbook Pro._<br>\n",
    "<br>\n",
    "Briefly, the aims of this vignette and associated functions are to:<br>\n",
    "1. Estimate and apply dataset-specific filtering parameters.<br>\n",
    "2. Provide a set of robust and highly reproducible processing, filtering, and exporting functions for marker gene studies.<br>\n",
    "3. Faciltate transparency and reproducability of marker gene data analysis, regardless of user skill level.<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>A preface on filtering:</b> Filtering is an <i>essential</i> step in the analyis of marker gene datasets. This workflow uses a two-pronged approach (within sample and across sample) to filtering contaminants from read datasets. That is, we attempt to remove two types of contamination: <br>\n",
    "<br>\n",
    "1. Real biological sequences that have cross contaminated unassociated samples. <br>\n",
    "<br>\n",
    "2. Exogenous contaminants introduced during sample preparation. <br>\n",
    "<br>\n",
    "To achieve this, we first estimate and apply a <b>within-sample (WS)</b> threshold that taxa must exist above to remain in that sample. We estimate this threshold empirically by aligning amplicon sequence variant (ASV) nucleotide sequences to an external FASTA file of nucleotide sequences of each member of a positive control library, selecting the threshold that returns the appropriate alignment count. Next, we (optionally) remove control samples from the dataset and then apply several <b>across-sample (AS)</b> thresholds (relative abundance, prevalence, and/or coefficient of variation (CV)) to remove exogenous contaminants present as low abundance, stochastically represented, or invariant ASVs. \n",
    "</div>\n",
    "\n",
    "<br>\n",
    "<div class=\"alert alert-block alert-success\">\n",
    "<b>TIP:</b> Though this document follows a workflow for filtering out contaminant taxa from marker gene datasets, <b>microfilter</b>, <b>write.dataset</b>, and <b>write.dataset.biom can be used on any phyloseq-class dataset at any point, regardless of processing method, the number or presence of control samples, the marker gene sequenced, or if any filters have been applied.</b> \n",
    "</div>\n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Jump to section:\n",
    "[estimate.WSthreshold](#estimate.WSthreshold)<br>\n",
    "[plot.threshold](#plot.threshold)<br>\n",
    "[estimate.ASthreshold](#estimate.ASthreshold)<br>\n",
    "[microfilter](#microfilter)<br>\n",
    "[write.dataset](#write.dataset)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Before we begin...\n",
    "This workflow assumes that your sequencing project: \n",
    "-  has been converted into a __[phyloseq](https://joey711.github.io/phyloseq/)__ object.\n",
    "\n",
    "and ideally:<br>\n",
    "-  includes a mock community or other positive control of known composition. <br>\n",
    "-  has been processed with __[dada2](https://benjjneb.github.io/dada2/index.html)__ (this is not necessary, but we leverage the output of dada2 to align control sequences and write filtered FASTA files).<br>\n",
    "<br>\n",
    "Now, let's load some required packages and begin!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1] ‘1.24.2’"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "library(phyloseq); packageVersion(\"phyloseq\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“package ‘cowplot’ was built under R version 3.5.2”Warning message:\n",
      "“package ‘ggplot2’ was built under R version 3.5.2”"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[1] ‘0.9.4’"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "suppressMessages(library(cowplot)); packageVersion(\"cowplot\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“package ‘dplyr’ was built under R version 3.5.2”"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[1] ‘0.8.1’"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "suppressMessages(library(dplyr)); packageVersion(\"dplyr\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1] ‘3.1.1’"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "library(ggplot2); packageVersion(\"ggplot2\")\n",
    "theme_set(theme_bw()) #gray is a bummer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“package ‘tidyr’ was built under R version 3.5.2”"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[1] ‘0.8.3’"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "suppressMessages(library(tidyr)); packageVersion(\"tidyr\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1] ‘1.38.0’"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "suppressMessages(library(ShortRead)); packageVersion(\"ShortRead\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Getting started\n",
    "First, we'll need to source these functions into our R environment. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "source(\"/Users/bpb/Documents/GitHub/microfiltR/microfiltR_source_code.R\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's load the dataset and subset it to remove taxa not annotated at the Phylum level and identified as Chloroplast sequences."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "              Acidobacteria              Actinobacteria \n",
       "                         43                         345 \n",
       "            Armatimonadetes               Bacteroidetes \n",
       "                          1                         453 \n",
       "   candidate_division_WPS-1 Candidatus_Saccharibacteria \n",
       "                          4                          16 \n",
       "                 Chlamydiae                 Chloroflexi \n",
       "                          1                          18 \n",
       "        Deinococcus-Thermus                  Firmicutes \n",
       "                         18                         861 \n",
       "               Fusobacteria            Gemmatimonadetes \n",
       "                         50                           5 \n",
       "                Nitrospirae               Parcubacteria \n",
       "                          1                           2 \n",
       "             Planctomycetes              Proteobacteria \n",
       "                         13                         624 \n",
       "               Spirochaetes               Synergistetes \n",
       "                          4                           5 \n",
       "                Tenericutes             Verrucomicrobia \n",
       "                         13                           8 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#load the dataset\n",
    "e3 <- readRDS(file = \"/Users/bpb/Desktop/ECHO/Data/Combined_Run101218_Run101618/analysis/ECHO_2runs_Oct18.rds\")\n",
    "\n",
    "e3 %>%\n",
    "  subset_taxa(Phylum != \"NA\" & \n",
    "                Phylum != \"Cyanobacteria/Chloroplast\") -> e3\n",
    "\n",
    "table(tax_table(e3)[, \"Phylum\"], exclude = NULL)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For this vignette, we'll work with a subset of a recent study of vaginal swabs from a multinational African cohort. Let's take a look at the raw dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "phyloseq-class experiment-level object\n",
       "otu_table()   OTU Table:         [ 2485 taxa and 378 samples ]\n",
       "sample_data() Sample Data:       [ 378 samples by 9 sample variables ]\n",
       "tax_table()   Taxonomy Table:    [ 2485 taxa by 7 taxonomic ranks ]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "e3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our unfiltered object has 2,485 taxa, though some of those bugs are likely contaminants or irrelevent stochastic associates. We'll use some filtering functions to pare that number down to a smaller set of  bugs that we can interrogate with downstream analyses. <br>\n",
    "<br>\n",
    "## Filtering\n",
    "\n",
    "The first step in our workflow is to estimate the threshold at which our data suggest cross contamination exists. Because cross contamination cannot be corrected with standard global filters, we need to estimate the extent of cross contamination and apply our filter individually within each sample. We estimate this filtering threshold against a known positive control library (HMP Mock; HM-782D) of 20 taxa using the __estimate.WSthreshold__ function. However, due to operon variation along 16S, __we expect 25 unique ASVs along the region sequenced (V3-4)__. In addition to threshold estimation, __ws.threshold__ also performs a local alignment of each ASV sequence within your postiive control against an external fasta file to determine the number of exact matches between the actual composition of your sequenced control and its theoretical composition. <br>\n",
    "<br>\n",
    "\n",
    "<div class=\"alert alert-block alert-warning\">\n",
    "<b>Note:sequence alignment is only supported for datasets processed by DADA2 or those that have imported a nucleotide sequence file (eg. FASTA) into their phyloseq refseq slot.</b> DADA2 does not assign names to each ASV, but rather uses the nucleotide sequence as the identifier; we leverage this feature to perform sequence alignment and write output in FASTA format.\n",
    "</div>\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"estimate.WSthreshold\"></a>\n",
    "# estimate.WSthreshold\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>ESTIMATE.WSTHRESHOLD</b><br>\n",
    "Performs WS filter threshold estimation by iterative application over a range of thresholds. <br>\n",
    "<br>\n",
    "<b>Input:</b> <br>\n",
    "<b>ps:</b> a phyloseq-class dataset<br>\n",
    "<br>\n",
    "<b>Parameters:</b><br>\n",
    "<b>WSrange:</b> The range of WS filter thresholds to iterate over, followed by the estimation interval.<br>\n",
    "<b>controlID:</b> The sample ID of a positive control library, if applicable. Used for reporting ASV read count, taxonomy, and sequence alignment of taxa in the positive control.<br>\n",
    "<b>controlFASTA:</b> the path to a FASTA file of nucleotide sequences to be used for alignment to positive control sequences, if applicable.<br>\n",
    "<br>\n",
    "<b>Output:</b> <br>\n",
    "A dataframe of:<br>\n",
    "<b>threshold.value:</b> The WS threshold applied in that iteration. <br>\n",
    "<b>control.taxa.count:</b> The count of taxa in the given positive control. <br>\n",
    "<b>control.taxa.matches:</b> The number of perfect alignments between taxa in the given control and the controlFASTA file. <br>\n",
    "<b>read.count:</b> The read count in the positive control at the listed threshold value. <br>\n",
    "<b>read.percent:</b> The read percent (vs. pre-filter read count) in the positive control at the listed threshold value. <br>\n",
    "\n",
    "</div>\n",
    "\n",
    "<br>\n",
    "<div class=\"alert alert-block alert-success\">\n",
    "<b>TIP:</b> All of these functions support <b>vectorized input</b> for both convenience and ease of visualization! The format for the vectorized input used here is: <b>lower threshold:higher threshold, estimation interval</b>. For example, below, we will estimate over the range from 1e-5 to 2e-4 with an estimation interval of 1e-5.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Estimating filtering statistics from WS thresholds 1e-05 to 2e-04 by 1e-05\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A df[,5]: 20 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>threshold.value</th><th scope=col>control.taxa.count</th><th scope=col>control.taxa.matches</th><th scope=col>read.count</th><th scope=col>read.percent</th></tr>\n",
       "\t<tr><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.00001</td><td>28</td><td>25</td><td>13698507</td><td>99.99951</td></tr>\n",
       "\t<tr><td>0.00002</td><td>28</td><td>25</td><td>13698047</td><td>99.99615</td></tr>\n",
       "\t<tr><td>0.00003</td><td>28</td><td>25</td><td>13697298</td><td>99.99069</td></tr>\n",
       "\t<tr><td>0.00004</td><td>28</td><td>25</td><td>13696500</td><td>99.98486</td></tr>\n",
       "\t<tr><td>0.00005</td><td>27</td><td>25</td><td>13695537</td><td>99.97783</td></tr>\n",
       "\t<tr><td>0.00006</td><td>27</td><td>25</td><td>13694424</td><td>99.96970</td></tr>\n",
       "\t<tr><td>0.00007</td><td>27</td><td>25</td><td>13693231</td><td>99.96100</td></tr>\n",
       "\t<tr><td>0.00008</td><td>27</td><td>25</td><td>13692359</td><td>99.95463</td></tr>\n",
       "\t<tr><td>0.00009</td><td>27</td><td>25</td><td>13691054</td><td>99.94510</td></tr>\n",
       "\t<tr><td>0.00010</td><td>26</td><td>25</td><td>13689760</td><td>99.93566</td></tr>\n",
       "\t<tr><td>0.00011</td><td>26</td><td>25</td><td>13688361</td><td>99.92544</td></tr>\n",
       "\t<tr><td>0.00012</td><td>26</td><td>25</td><td>13687044</td><td>99.91583</td></tr>\n",
       "\t<tr><td>0.00013</td><td>26</td><td>25</td><td>13685916</td><td>99.90760</td></tr>\n",
       "\t<tr><td>0.00014</td><td>26</td><td>25</td><td>13684498</td><td>99.89724</td></tr>\n",
       "\t<tr><td>0.00015</td><td>26</td><td>25</td><td>13683125</td><td>99.88722</td></tr>\n",
       "\t<tr><td>0.00016</td><td>26</td><td>25</td><td>13682026</td><td>99.87920</td></tr>\n",
       "\t<tr><td>0.00017</td><td>25</td><td>25</td><td>13680575</td><td>99.86861</td></tr>\n",
       "\t<tr><td>0.00018</td><td>25</td><td>25</td><td>13679073</td><td>99.85764</td></tr>\n",
       "\t<tr><td>0.00019</td><td>25</td><td>25</td><td>13677622</td><td>99.84705</td></tr>\n",
       "\t<tr><td>0.00020</td><td>25</td><td>25</td><td>13676524</td><td>99.83903</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A df[,5]: 20 × 5\n",
       "\\begin{tabular}{r|lllll}\n",
       " threshold.value & control.taxa.count & control.taxa.matches & read.count & read.percent\\\\\n",
       " <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t 0.00001 & 28 & 25 & 13698507 & 99.99951\\\\\n",
       "\t 0.00002 & 28 & 25 & 13698047 & 99.99615\\\\\n",
       "\t 0.00003 & 28 & 25 & 13697298 & 99.99069\\\\\n",
       "\t 0.00004 & 28 & 25 & 13696500 & 99.98486\\\\\n",
       "\t 0.00005 & 27 & 25 & 13695537 & 99.97783\\\\\n",
       "\t 0.00006 & 27 & 25 & 13694424 & 99.96970\\\\\n",
       "\t 0.00007 & 27 & 25 & 13693231 & 99.96100\\\\\n",
       "\t 0.00008 & 27 & 25 & 13692359 & 99.95463\\\\\n",
       "\t 0.00009 & 27 & 25 & 13691054 & 99.94510\\\\\n",
       "\t 0.00010 & 26 & 25 & 13689760 & 99.93566\\\\\n",
       "\t 0.00011 & 26 & 25 & 13688361 & 99.92544\\\\\n",
       "\t 0.00012 & 26 & 25 & 13687044 & 99.91583\\\\\n",
       "\t 0.00013 & 26 & 25 & 13685916 & 99.90760\\\\\n",
       "\t 0.00014 & 26 & 25 & 13684498 & 99.89724\\\\\n",
       "\t 0.00015 & 26 & 25 & 13683125 & 99.88722\\\\\n",
       "\t 0.00016 & 26 & 25 & 13682026 & 99.87920\\\\\n",
       "\t 0.00017 & 25 & 25 & 13680575 & 99.86861\\\\\n",
       "\t 0.00018 & 25 & 25 & 13679073 & 99.85764\\\\\n",
       "\t 0.00019 & 25 & 25 & 13677622 & 99.84705\\\\\n",
       "\t 0.00020 & 25 & 25 & 13676524 & 99.83903\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A df[,5]: 20 × 5\n",
       "\n",
       "| threshold.value &lt;dbl&gt; | control.taxa.count &lt;dbl&gt; | control.taxa.matches &lt;dbl&gt; | read.count &lt;dbl&gt; | read.percent &lt;dbl&gt; |\n",
       "|---|---|---|---|---|\n",
       "| 0.00001 | 28 | 25 | 13698507 | 99.99951 |\n",
       "| 0.00002 | 28 | 25 | 13698047 | 99.99615 |\n",
       "| 0.00003 | 28 | 25 | 13697298 | 99.99069 |\n",
       "| 0.00004 | 28 | 25 | 13696500 | 99.98486 |\n",
       "| 0.00005 | 27 | 25 | 13695537 | 99.97783 |\n",
       "| 0.00006 | 27 | 25 | 13694424 | 99.96970 |\n",
       "| 0.00007 | 27 | 25 | 13693231 | 99.96100 |\n",
       "| 0.00008 | 27 | 25 | 13692359 | 99.95463 |\n",
       "| 0.00009 | 27 | 25 | 13691054 | 99.94510 |\n",
       "| 0.00010 | 26 | 25 | 13689760 | 99.93566 |\n",
       "| 0.00011 | 26 | 25 | 13688361 | 99.92544 |\n",
       "| 0.00012 | 26 | 25 | 13687044 | 99.91583 |\n",
       "| 0.00013 | 26 | 25 | 13685916 | 99.90760 |\n",
       "| 0.00014 | 26 | 25 | 13684498 | 99.89724 |\n",
       "| 0.00015 | 26 | 25 | 13683125 | 99.88722 |\n",
       "| 0.00016 | 26 | 25 | 13682026 | 99.87920 |\n",
       "| 0.00017 | 25 | 25 | 13680575 | 99.86861 |\n",
       "| 0.00018 | 25 | 25 | 13679073 | 99.85764 |\n",
       "| 0.00019 | 25 | 25 | 13677622 | 99.84705 |\n",
       "| 0.00020 | 25 | 25 | 13676524 | 99.83903 |\n",
       "\n"
      ],
      "text/plain": [
       "   threshold.value control.taxa.count control.taxa.matches read.count\n",
       "1  0.00001         28                 25                   13698507  \n",
       "2  0.00002         28                 25                   13698047  \n",
       "3  0.00003         28                 25                   13697298  \n",
       "4  0.00004         28                 25                   13696500  \n",
       "5  0.00005         27                 25                   13695537  \n",
       "6  0.00006         27                 25                   13694424  \n",
       "7  0.00007         27                 25                   13693231  \n",
       "8  0.00008         27                 25                   13692359  \n",
       "9  0.00009         27                 25                   13691054  \n",
       "10 0.00010         26                 25                   13689760  \n",
       "11 0.00011         26                 25                   13688361  \n",
       "12 0.00012         26                 25                   13687044  \n",
       "13 0.00013         26                 25                   13685916  \n",
       "14 0.00014         26                 25                   13684498  \n",
       "15 0.00015         26                 25                   13683125  \n",
       "16 0.00016         26                 25                   13682026  \n",
       "17 0.00017         25                 25                   13680575  \n",
       "18 0.00018         25                 25                   13679073  \n",
       "19 0.00019         25                 25                   13677622  \n",
       "20 0.00020         25                 25                   13676524  \n",
       "   read.percent\n",
       "1  99.99951    \n",
       "2  99.99615    \n",
       "3  99.99069    \n",
       "4  99.98486    \n",
       "5  99.97783    \n",
       "6  99.96970    \n",
       "7  99.96100    \n",
       "8  99.95463    \n",
       "9  99.94510    \n",
       "10 99.93566    \n",
       "11 99.92544    \n",
       "12 99.91583    \n",
       "13 99.90760    \n",
       "14 99.89724    \n",
       "15 99.88722    \n",
       "16 99.87920    \n",
       "17 99.86861    \n",
       "18 99.85764    \n",
       "19 99.84705    \n",
       "20 99.83903    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#load a FASTA file of full length 16S sequences for each operon of each community member\n",
    "mock.fasta <- \"/Users/bpb/Desktop/microfiltR/HMP_MOCK.v35.fasta\"\n",
    "\n",
    "(ws.threshold1 <- estimate.WSthreshold(ps = e3, WSrange = c(1e-5:2e-4, 1e-5), controlID = \"185\", controlFASTA = mock.fasta))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can take a quick peek at a visual summary with the plotting function, __plot.threshold__."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"plot.threshold\"></a>\n",
    "# plot.threshold\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>PLOT.THRESHOLD</b><br>\n",
    "Plots the results of threshold estimation for both WS and AS filters over the specified range. <br>\n",
    "<br>\n",
    "<b>Input:</b> <br>\n",
    "<b>est.obj:</b> the output from either threshold estimation function.<br>\n",
    "<br>\n",
    "<b>Parameters (only needed for taxonomic visualization plots):</b><br>\n",
    "<b>x:</b> The AS threshold to be plotted on the x-axis.<br>\n",
    "<b>y:</b> The AS threshold to be plotted on the y-axis.<br>\n",
    "<b>taxrank:</b> The taxonomic rank at which to facet the output plot.<br>\n",
    "<b>PFT:</b> The prevalence filter threshold to be visualized with a solid or dashed black line (depending on the associated axis).<br>\n",
    "<b>CVT:</b> The coefficient of variation filter threshold to be visualized with a solid or dashed black line (depending on the associated axis).<br>\n",
    "<b>RAT:</b> The relative abundance filter threshold to be visualized with a solid or dashed black line (depending on the associated axis). <br>\n",
    "<br>\n",
    "<b>Output:</b> ggplot2-class plots of dataset statistics over WS and AS estimation ranges. <br>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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J5OQCknT55MT09n3CnP80Sk1+vZ9+t0OnU6nUe6Jlwyq35xyWWqWbPmvffeq2hW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Ru57QbmzuQ4HTFWCRtYXdm2++2aNHj8uX\nLxPR0KFDr169OmXKlPXr1x86dKhp06alpaX/+c9/2rVrd+jQIXtmCyIjXNhhKxZcxWeffbZj\nx46IiAgfHx+ZTObn5zd27NjExMSyPUQqO7KaE9WrV+/MmTOLFi1q166dh4eHj49PSEjI999/\nv2nTJns3fQDRwW6sTVl7KnbdunVEVK9evdWrV48ePdr8et++fa9cuTJ37ty1a9fevHmzX79+\nFbbOA7CWYGEnwYoduJDhw4cPHz7chiOvXLlSzYnc3d3fe++99957z5rBAFUXEkmfv8V/b+zP\nNHUNzsZarxJbsWPGjLl27VrZqs7Ew8NjzZo1sbGxrVq1smluIHoSJUl52yBx+nyWuQAAgF14\n+VKHcN5ozgO6eIxdMjWftYXdnj17Nm/eLHBfTUhIyKVLl2bPnm2jxACISLDjiRY9igEAXILw\nbuzxH1nl4QqsLewGDx4sPECr1U6cONGuvblBjAR6FOMZOwAA1xASKXQ29uQO0qFxqbWsfcbO\nRK/X37lzx3QnyRPS09M3bdqkVCo/+eQTG+UGINTKTqLLs/st1gAAwEDtetShFyXynL8syKZf\nD1C3IWxzqqkqUdjt3LlzypQpDx48EBjTqFGjaqcEUIbQViwOTwAAuIpeo3kLOyI6/iMKOytZ\nu3OakpIyevRogapOIpF06NBh48aNNkoMgIgECztdPhmxZgcA4BKCI0mu5I2e2kUlhQyzqcGs\nLezWrl2r0WgiIiLS0tJOnjypVCq7du2akZFx+/btgwcPhoSEyOXyjz/+uPzd0gDVInT5hJHT\nFbDLBAAA7EftRc8N4I2WFNLZJy8vBousLewOHz5MRIsWLWrcuHFwcHD37t3Pnj1rMBj8/f0j\nIiKOHDkSGBg4duzYjIwMe2YL4oPLJwAARCL8yX5qf4OzsdaxtrBLT08noqCgINOnAQEBRHT+\n/HnTpwqFYu7cuTk5OVFRUXZIEkRM8LpYQscTAACX0f0FclPzRhN+oQL8nV8xaws7jUZDRCrV\nn91iTYXdjRs3zAP69OlDRLt27bJxgiByCm+BIDqeAAC4DqU7deXvraYtpVPRDLOpqawt7EzH\nXW/evGn61FTYJSYmmge4u7sTUVpamo0TBJETXLHDViwAgEsR3o09sZVVHjWYtYVdz549iWjh\nwoVarZaIunfvTkS//PJLdna2aUBMTAwRubm52SVNEC2ZJ0l4m/JgxQ4AwKV0eZ48fXijiYcp\nR6jnGpD1hd3kyZM5jtuyZctTTz1FRE2bNu3QoUNeXl54ePgXX3zx0UcfTZgwgf7akAWwGY4j\neS3eIFbsAABciUxBPYbyRvU6ivuZYTY1krWFXadOndauXevu7v748WPTK2vXrpVKpZcvX546\ndeqHH35YUFDg5eW1ePFiu6UKYiWwG6vBg7QAAK4FZ2OrpxJXu7755puZmZknTpwwfRocHHzg\nwIHQ0FC1Wu3t7R0ZGXn27NmWLVvaJ08QMf5bxTgdVuwAAFxLxz7kXZ83euUkPUpnmE3NU7m7\nYtVqdVhYmPnTPn36YO8V7E7o8gk8YwcA4FokUgodQbvXWo4aDXTiJ3pxJtucahKhFbvjx48f\nP36cVSYAPPi3YvGMHQCACwp/SSiK3VhBQit2vXr1IiKj0cgqGQBLBJ6xM2hIV0Qyd4bZAACA\nnbUNofpNKJOngVryObr7OzXEo1+WVeIZOwDHUAr1KCYs2gEAuBiOo7CRQgPQ0I4fCjtwesK3\niuFgLACA6xE+G3t0M6s8ah4UduD0+E/FEuG6WAAAV9SyMzVqxRu9fZ1uXWGYTU2Cwg6cHv+p\nWCJsxQIAuKieOEJRFRW3O7l//36lvqKfn19VkwGwRF6bOI74DvFgKxYAwCX1/gdtWsgbPbaF\nhr3DMJsao+LCznSHmPVwihZsTCInqTvpCi1HUdgBALgk/9YU8DSlXrYczUiVpiRqmzzNNqca\nAFuxUBMI7MZiKxYAwFUJHqGQn8S9sRZUvGK3Zs0aBnkACJHXJrprOYQVOwAAV9XrH7ThPb5H\ncRSndtCYDxhn5PwqLuzeeustBnkACBE4GItTsQAArqp+EwrsQjfOWgxy2fflyWepY2/GSTk5\nbMVCTYCtWAAAcRLcjVWe3skskZoChR3UBAI9inUFZNQxTAUAABgKf4kkUr6g4uxu0mlZpuP8\nUNhBTSCwYmc0kgaLdgAALsrnKWofxheU5GdJLx9nmE0NgMIOagL0KAYAEK1egmdj43E29m+E\nDk9MnjyZWR4AQoRvFdNks8oDAACYCxtJn/+LdBqLQemZ3VRaTEo3xkk5LaHCbt26dczyABAi\n8IwdYcUOAMClqb2pU19K+MVikCvOp3MxFBLJOCmnha1YqAmEt2LRyg4AwLUJno3FvbFlobCD\nmkDmQRIFbxQrdgAAri14mNBm65k9VJTHMBunhsIOagh5Ld4QVuwAAFybmyd1Gcgb1ZTQmT0M\ns3FqKOyghkCPYgAAMRPejT2G3dg/obCDGkLgYCxOxQIAuLyug8mD/yDd+QOU95hhNs4LhR3U\nEAIHY7FiBwDg8hQq6v4Cb1SnpXhcL0aEwg5qDKU3b0ibS0Yjw1QAAMARKtiN3cIqD6eGwg5q\nCIEVO4OOdAUMUwEAAEfoFEG16vBGLx2jOzcYZuOkUNhBDYEexQAAIieTU8iLvFGjkXavZZiN\nk0JhBzVEBdfFouMJAIAICN4bSwc3UqHYf85HYQc1RAXXxaKwAwAQgad7Uv0mvNHifDqwgWE2\nzgiFHdQQ2IoFAABOQkP+KTQgejUZ9KyycUaOKeweP378/vvvd+zY0cfHR6lUNmzYMDIy8tCh\nQxYHnzhxYtiwYb6+vgqFwtfX9/nnn9+7dy/jhMHxFLWJON4oVuwAAERi4CRSefBG7/9BCb8w\nzMbpOKCwu3jxYps2bRYtWnTx4sXs7GyNRnPv3r2dO3f269dv/vz5Twz++OOPw8PDd+3a9fDh\nQ61W+/Dhw/379w8ZMmTFihXsMwdH4qQk9+SNorADABAJtTf1His0IHo1q1ScEevCTqvVRkZG\nPnjwoFGjRlu3bn38+HFeXl5cXFxwcDARLV68ePfu3ebB0dHR7733HhGNGzfu2rVrJSUlV69e\n7d+/PxHNnTv3999/Z5w8OBh6FAMAABENf5s4/j2cxMP0RxLDbJwL68IuOjr6jz/+kMlkhw4d\nGjVqlI+Pj6enZ0hIyKFDh1q1akVECxcuNI00GAzvvPMOEY0fP/67774LCgpSKpVt2rSJjo5u\n2LChVqv9+uuvGScPDqYQ6FGMFTsAANFo0oae6S00QMR9T2SM5zt69CgRhYeHt27duuzrbm5u\n//jHP/7zn/+cP3++oKBArVYfO3YsJSXFzc1t+fLlZUeqVKqXXnppxYoV586dY5o6OJzAil3B\nH3T5fTZZKDQaIiKFgs10ZsrSUpleL5PJKje1zIPqPEe+4cRJ7ZYaAABzw6bRhSO80cPf02uL\nhboZuy7Whd3t27eJKCgoqHyoYcOGRGQ0Gs2FHRE9//zzPj4+T4xcvnz5E9UeiIJAKzt9CWVf\nZJOFRKcjIpKx/rMj1ek4g0EikVR66ofxdC+G2n0o9JAiAEDN0m2wwa+Z5P4flqOlRXTg/2jk\nu2xzcgqst2L37dtnNBpXr7bwYOPx48eJqFatWvXq1SOiuLg4IurWrdvdu3enTJnStGlTpVLp\n6+sbGRlpCoHoCPcoBgF5yfRblKOTAACwHU6iGTBJaMCuz0mvY5WNE2G96sBny5YtW7ZsIaKx\nY8dKpVIiSk1NJaLs7Ox27drl5Pz5BNXDhw937txpOlRhfhrPpKioKC0tzfypVquVyWQ6HdPf\nVIPBQESMJyUio9Fo+i/7qVm+ZU6ilhiNT7xoLPcKG46at+pTPzyjz/uD3P2r8EtrxDe2A39H\nAMAhNH1eUW79hCvOtxx+cJtO76aQSLZJOZ7jC7vS0tIPP/zws88+MxqNLVu2XLRoken17Oxs\nIvr000/d3NyWLl06YsQIPz+/69evz58//5dfflm0aFHr1q3Hjv3fgefr169PnjzZ/GlQUJCP\nj4+5ImRJY3oGizmtVuuQ90us3rKsVOqu1ZZ9xWAwmGoO9hw4b5WnLr73q7Zu1XdjHfWNrdFo\nrJla+/fvDQBweUaVujR0lOrget4R0atFWNg5+OaJEydOdOzY8dNPPzUajSEhIbGxsaYn6rRa\nbWFhIREZjcaYmJh33nmnadOmKpWqY8eO0dHRLVq0IKIlS5Y4NnlgzCh/8mlLqBSJDmeHAcCl\nFA94gzj+SubyCUq9xDAdp+CwFbvHjx/PmjVr48aNROTu7r5gwYIZM2aYNmGJSCL58/cpJCQk\nNDS07C+Uy+X//Oc/Z86ceeXKlaysLPPRinbt2u3atcs8bNmyZVKp1Nubv0GGHRQVFRGRu7s7\ny0mJqKCgQKvVyuVytVrNeGqmb7m2WnK7NumKiEiv1xsMBolEYv6eYUav1xORQ+at5luWKXTu\nVfoT4dhvbIVC4eHB32X+L3K5nEFKAOBU9H4B+o59pImWb64iItq5mmbxL+m5IscUdnFxcS+9\n9FJGRgYRjRo1aunSpY0bNy47QCqVuru7FxUVtW3btvwv79Spk+mDzMxMc2FnuprMPEYmkxHz\nf305jmM/qXlejuMcNTWjeaVS8n+Rbv1QPgH2HDVvdabmdHlUpd+pGvGN7cDfEQBwIM3AKW4C\nhd3RTfT6J+TlyzAjB3PAVuyxY8ciIiIyMjKaNm16+PDhrVu3PlHVmTRv3pyIcnMt3ChgfuCG\n/RICOFjjkeQX4egkaixcvAYALkffMYL8W/OGtaUU81+G6Tge6xW7vLy8MWPGlJaWPvfcc/v3\n7y/fo86sS5cuSUlJiYmJRqPxiZ/FL1y4QETe3t7+/tUlzoIAACAASURBVFU54gc1GCehwGlU\nv5fuziFD0X2ZlGPfKNjgoAbF+tJSvTUNigvTSJNtOYSL1wDA9XAcvTCV1v6Ld8DutTTyXZKJ\n5WkN1oXdxo0bMzMzfX19d+/eLVDVEdHLL7+8fv365OTk77///pVXXjG/XlxcvGbNGiIaPXq0\n+VE8EBev9hpJE41Go1QqFZ6sm+5qCgqISMH8ccbSvDyr3vLvX9C9GMshrNgBgEvqN56+nU+F\nPD+7Pr5H8Tuo50tsc3IY1oXR1q1biejNN9/08/MTHhkeHj548GAimjJlSlRUVGZmpkajSUxM\nHDhwYHp6ep06dd5/n9EVUgA1iVzgfo4CMoixXScAuDg3NfWfIDRgp4VrEVwV08JOr9ebLnhd\nsGABx6+kpMQ0/vvvvw8PDy8uLp4+fbqfn59SqezcufPx48dr1aoVHR391FNPsUweoGYQuJ/D\naCRdHsNUAABYGT6NJPynrK6douQEhtk4EtPCLi0trVI9Tr28vA4fPrx+/frg4GBPT0+VStWy\nZctp06Zdv349JCTEfnkC1GDy2kJR7MYCgEuq35S6DhIasOtzVqk4GNNn7AICAip77Y9UKp0w\nYcKECYJLrABgJnyjLgo7AHBVw6bR6d280eNbaeJn5FPBY2AuAIcPAFyLcGGHg7EA4Ko69qGA\np3mjOg3tW8cwG4dBYQfgWgQOTxCRFit2AOC6hvxTKLrnS9KUsErFYVDYAbgWmQdJ+Ns1YSsW\nAFxY33FUqw5vNOcBxW5jmI1joLADcDkC5yewFQsALkzpTgNeFxqwYxWrVBwGhR2AyxEo7LBi\nBwCu7YWpJOU/GHozka6dZpiNA6CwA3A5AucnUNgBgGvzbUw9hgoNiHbxZsUo7ABcjkBhh61Y\nAHB5w6YJReO206N0Vqk4AAo7AJcjcDBWk0OV7CUJAFDDtA+j5s/wRvU62uvKfU9Q2AG4HIFn\n7Iw60hcyTAUAwBGEF+0ObnThH3FR2AG4HPQoBgCR6zWGatfjjT5Kp+tnGGbDFAo7AJcjfF1s\naTarPAAAHEShokFvCA04+TOrVFhDYQfgcrBiBwAwaDJx/EVO3M+uuhuLwg7A5VRQ2KHjCQCI\nQD1/CurGG828Rb+fZ5gNOyjsAFyOvDYRxxvVYMUOAMQh9EWhqIvuxqKwA3A5nJRkat4oVuwA\nQCTCRhLH/1PuiZ8YpsIOCjsAV4QexQAA9fyp1bO80YxUSr3EMBtGUNgBuCKBwg6nYgFAPEIE\nd2PjXHA3FoUdgCsS6HiCFTsAEI+wkUJRV9yNRWEH4IoU3rwhPGMHAOLxVIDQ9WLpyZR2jWE2\nLKCwA3BF8lq8IV0RGTQMUwEAcCjhs7Fx21nlwQgKOwBXJEePYgAAIqpoN9blmp6gsANwRcI9\nijXYjQUA0WgUSE3a8kZTL1N6MsNs7A6FHYArQmEHAGBWQafiHazyYAGFHYArEjgVS9iKBQCR\nEVPTExR2AK5I4FQs4WAsAIhMwNPk35o3+vt5ykhlmI19yRydAADYgVRFEiUZSi1HsRUL9mQ0\nGolIr9fbbwqDwWDvKcyzmCYyvSk7YfB/rCyDwWDvuYxGI5tZTP+1ZiJJj2Hc1iV8UUPsduOI\nWQITWTlLdZT9fhMYVuG3Igo7ABclr02lDyyHsBUL9qTX6w0GQ3a23e84YTCFSW4uiz8yeXl5\nDGYhosLCwsLCQnvPUlRUVFRUZO9ZiKi0tLS0lOeH2DJkT/f1EirstuX0mSD8FTQaFo2iKvyz\no9Vqhb8CCjsAF6X05i3ssGIH9iSTyYioTp069puitLS0uLjYy0vwkFC1aTSa/Px8IvL29pZI\n7PjkktFozMrK8vLykkql9puFiB4/fkxEarVaqVTadaLc3FylUqlSqew6S15enlarValUHh4e\nFY+u05saNKd7KRaDspvn6+gLybexxWhxcbFer1er1dXJtkJFRUXFxcUSicTbW+hZGoVCIfx1\nUNgBuCiB8xMo7MD+OI6z9xe36xRlvz7Hcfaei9kszCZi9nbI+u+E4EjattRyyGjkTkXT8Ldt\nMEtVlf1+q87XweEJABeF62IBAMqq4AoKFzkbi8IOwEUpBa6LzSWy45PgAADOKLAL32YrEdHV\neHp8j2E29oLCDsBFyfhX7IwG0jJ6TBsAwFlwHIVE8kaNBjoVzTAbe0FhB+CihC+fwG4sAIiQ\nCDoVo7ADcFG4VQwA4Alte1CdBrzRyycoh6eZQM2Bwg7ARQnfKobCDgBEiJNQ8HDeqEFPp3Yx\nzMYuUNgBuCis2AEAlCd8NvZkjd+NRWEH4KLktYjjb3aqwzN2ACBK7cPIy5c3evEo5WcxzMb2\nUNgBuCqO5J68QazYAYA4SaTUYxhvVKel07sZZmN7KOwAXJfAbixOxQKAaLl0p2IUdgCuS85f\n2GHFDgBEq0Mv8vThjSYeosIa/KMvCjsA14XrYgEAypPJqcdQ3qi2lM7uZZiNjaGwA3BdAlux\nKOwAQMxct1MxCjsA1yVQ2BlKSV/CMBUAAGfSOYLU/Bdqn4uh4nyG2dgSCjsA14UexQAAFskU\n1HUQb1RTQgkxDLOxJRR2AK6rgutiUdgBgIi5aKdiFHYArkvgVCyh4wkAiNuzA8iNv9nnmb1U\nUsgwG5tBYQfgurAVCwDAR6GiLgN5o6VFdP4gw2xsBoUdgOvCdbEAAAJcsVMxCjsA1yVRkMyd\nN4qtWAAQua6DSOXBGz29mzQ1r3sACjsAl4YexQAAfJTu9Gx/3mhxPl04zDAb20BhB+DSBM5P\n4FQsAIBwp+LY7azysBkUdgAuDZdPAAAI6D6EFCre6Jk9pNcxzMYGUNgBuDQUdgAAAtw8qVME\nbzQ/i5JiGWZjAyjsAFyawDN2+gIy1LCfRAEAbE/4bGz8TlZ52AYKOwCXJrBiZzSSNo9hKgAA\nTqnbEJLKeKPxO8loZJhNdaGwA3Bpwj2K0fEEAMDTh9qH8UYf3ZXcTGSYTXWhsANwaRXcKobH\n7AAAiHoMEwhKz+5hlkj1obADcGm4fAIAoEIhkcRxfEHpmd0sc6kmFHYALg2FHQBAheo2pJad\n+YKS9GTJ3d9YplMdKOwAXJrUgzj+h4LxjB0AgEnwcIGg7OxeZolUEwo7AJfGcaTArWIAABWp\noLCrMY/ZobADcHW4VQwAoEKNg6hRIF9QmpJID++wTKfKUNgBuDqBx+ywFQsAYBbMfzbWaKTT\nNeMIBQo7AFcn0MoOW7EAAGaCu7F0KppVHtWCwg7A1Qmv2NWojuoAAHYU2IXqNuKNXj5B+VkM\ns6kiFHYArk6gsDNoSV/EMBUAACfGcdT9Bd6oTktn9zHMpopQ2AG4OuFbxbAbCwBgJrwbG7+T\nVR5Vh8IOwNXhVjEAACs93ZPU3rzRXw9QSSHDbKoChR2AqxO+fAIHYwEAzGRy6jqIN1paRImH\nGGZTFSjsAFwdtmIBAKxXwW6ss5+NRWEH4OrktQUut0ZhBwDwN88NIKU7b/TMHtLrGGZTaSjs\nAFydREYyNW8UW7EAAGUp3alzBG80P4uSYhlmU2ko7ABEAD2KAQCsV5PPxqKwAxABXBcLAGC9\nbkNIKuONxu905tbuKOwARADXxQIAWM/Th9qH8UYf3aXffmWYTeWgsAMQAYHCDluxAADl9Rgm\nFHXie2NR2AGIgMAzdrpCMmgYpgIAUBOERAr1E3Dix+xQ2AGIQAU9ivNY5QEAUEPUbUgtO/NG\nb1+nOzcYZlMJKOwARKCCHsXZrPIAAKg5amanYhR2ACJQwXWxOD8BAFBOzWx6gsIOQARwXSwA\nQGU1DqJGgbzR387RwzsMs7EWf5uWGs5oNBKRTsf03g+DwcB+UvrrzRqNRvZT4y0zU623LFFL\n+bsuGYoeGQW/Zo14y0YnbisFADVV8DDa+qnlkNFIp3fTC1PZJlQxly3s9Hq9wWDIyXFAKweN\nxjFnDLVarUPeLznuLWs0GgdO7ah5qzZ1LT3Hd/pVk3e/xIrvHCd/y1qtlkEyACAuwcN5Czsi\nOhWNwo4dmUxGRHXr1mU5aUFBARGp1fz3ctpHXl6eRqNRKBS1atViPLVj37JSqfT09GQ8dU19\ny2pfKnlgMaJQ6tWCf1JqxFtWKBQMUgIAcQnsQnUb0aN0y9HLJyg/izx92OZUATxjByAOAucn\ncCoWAMAijqPuL/BGdVo6u49hNlZBYQcgDgIdT3B4AgCAT007G4vCDkAccKsYAEAVPN3TqPbm\njf56gEoKGWZTMRR2AOIgUNhpc4lwpBQAwBKZXP/sAN5oaRElHmKYTcVQ2AGIg8BWrNFA2nyG\nqQAA1CT6rkOEwk52BQUKOwBxQI9iAIAq0XeKMCrceMNn9pCedZtPASjsAMRB+FYxHIwFAOCj\ndNc/05s3mp9FSbEMs6kACjsAcRDYiiWs2AEACNFVsBvrRGdjUdgBiIOS/1QX4WAsAIAQ3bPP\nk5T/Tof4neQ0txqisAMQB5kncfx/3lHYAQDwM6q9qX0Yb/jRXfrtV4bpCEFhByAOnIRk/Bdz\nYSsWAEBYj2FCUafZjUVhByAa6FEMAFBlwcOI43ijJ3cwTEUICjsA0RDqUYzCDgBAUD1/atmZ\nN5qeTH8kMcyGFwo7ANHAdbEAANUREikUPfkzqzyEoLADEA0F/8FYbMUCAFQodIRQNA6FHQCw\nJLBipy8hfQnDVAAAaqCGLalZe97orSt0+zrDbCxDYQcgGrhVDACgmkJeFIo6wREKFHYAoiFc\n2GE3FgCgQmGCu7FO8JgdCjsA0RC+VQyFHQBAhZq0pcZBvNGbF+jeTYbZWIDCDkA0KtiKRWEH\nAGAF596NRWEHIBpyPGMHAFBtoYKFnaPPxqKwAxANiYKkbrxRbMUCAFij+TPUoAVv9LdzlJnG\nMJsnobADEBOhyyewYgcAYB2BRTujkeIduRuLwg5ATHBdLABA9Qk/ZufQ3VgUdgBiInAwFoUd\nAICVAp8jv2a80Wun6OEdhtn8DQo7ADEROD+BU7EAANYLHs4bMhrp1C6GqfwNCjsAMRHYitXl\nk1HPMBUAgJpM+Gys4zoVo7ADEBOBrVijkbR5DFMBAKjJgrpTPX/e6OVYyspgmM3/oLADEBPc\nKgYAYBMcR8HDeKNGA53ezTCb/0FhByAmFVw+gY4nAABWc8qzsSjsAMQE18UCANhK+1DyeYo3\neukY5T5kmM2fUNgBiEkFt4qhsAMAsBonoR5DeaN6HZ3ZwzCbP6GwAxATmZokMt4otmIBACrF\n+XZjUdgBiAnHkawWbxRbsQAAlfJML6pdjzeaeIgKshlmQ4TCDkB0cKuYU0pJSXnjjTeaNWum\nUqnq168fFha2YcMGnU5XnZEW3bx5880332zVqpWbm5u7u3vr1q2nTZt2+/btJ4bFxsZy/O7f\nv1/dNwzgGiRS6v4Cb1SnpTN7GWZDRMS/KQMALkmgsMNWrIMcOXJkyJAhxcXFpk8fPHjw4MGD\nuLi4n376afv27R4eHlUYadGBAwdefPHFwsJC8yvJycnJyckbN27ctWtXeHi4+fXU1FRbvTsA\nFxf6Iu1fzxs9+TP1HccwG6zYAYiN0HWxrLcMgIju378/cuTI4uLijh07Hj9+vLi4+NatW8uW\nLXN3d9+/f//s2bOrMNKix48fjx49urCwsHPnznFxcXl5eZmZmVu3bm3YsGFeXt7IkSNzcv63\nZJuSkkJEa9asMVri5+dnp/8bADVPx76k9uaNnttPRUx7v6OwAxAZoetisWLnAEuXLs3Ozvbx\n8Tl8+HDPnj1VKlWTJk1mzZr1448/EtFXX3118+bNyo60aNu2bTk5OQqFYs+ePSEhIZ6enr6+\nvqNGjdq+fTsRPXr0aO/e/+0ZmQq7li1b2u+NA7gImZy6D+GNaksp4ReG2aCwAxAbga1Yg5Z0\nhbxRsI+ff/6ZiN566y0fH5+yrw8ZMiQgIECv1+/evbuyIy1KS0sjombNmj311N86b3Xt2lWp\nVBJR+RW7Vq1aVeOdAYiGM52NRWEHIDLCPYqxaMdWYWGhqd7q0KFD+WhQUBARHTx4sFIj+TRv\n3pyI/vjjj8zMzLKvx8XFlZaWElHbtm3NL6akpCgUisaNG1f6LQGI0LP9yZ2/4UDCL1TC7mdm\nFHYAIoPrYp2JRqMxfeDu7l4+ajQaiejOnTuVGsnnpZdeatasmUajiYiI2L9/f25u7qNHj7Zu\n3Tp69GgiCg4O7tWrl2lkXl7e48ePmzdvvmPHjvDwcC8vL5VK1bJly2nTpglPASBSciV1HcQb\nLS2ic/uZ5YJTsQAig8LOmXh5eXl4eBQWFv7+++8DBgx4IpqcnExEjx49qtRIPp6enkePHp06\ndeovv/zy/PPPlw2NGDHim2++MX9q2odNTk4eNWqU+cWbN2+uWbNm48aNW7ZsGThwYNlfnpqa\n+vXXX5s/zcnJUavV+fn5Fb//qjIYDAaDwa5TmGYxfVBQUMBxnF3nIqLCwkIGsxBRSUmJ+ecE\nOzEYDCUlJVqt1q6z6PV6ItJqtfb+TtDr9UajUXgWWeeBbse28EW1x34seaaf8CympkUVTlRh\nbyMUdgAig1vFnAnHcb17996zZ8+6deumTp0qkfxvF2Xv3r2mAsu0T2r9SAHXr1+/du1a+ddP\nnTp1+vRpc7Vn+moGg6FDhw5Lly7t0aNHSUnJvn375syZc//+/REjRiQkJLRr1878y7Ozsw8f\nPmz+NCgoyN3dvcJkqo/BFCb2LoNYzkJE9q63TAwGg/XtFatDr9ebKjwGEwlENe16qpTuXGmR\nxajs1xhNQZ5RrqxwFqPRKPyNbf55gw8KOwCRkdcmjiOj0XIUz9gxN3fu3H379l27dm3kyJEf\nfvhh69atMzIyNm/evHjxYolEYjAY6tatW9mRFh07dmzo0KFarbZjx45Llix57rnnNBrNmTNn\n/v3vf1+/fn3IkCHHjh0LDQ2lvwq7Ll26HDt2zLTz6+Hh8corr4SGhnbq1CknJ+eDDz7YsWOH\n+St7e3v37dvX/Onjx48lEonpQIadmIoGhUJhvylMs5hqIIVCYe+1tNLSUjazEJFcLi/7g4E9\naLVaiUQilUrtPYvBYJBKpTKZfYsZ04pdBbMolfpO/WSnoy0GuZJC9+sndc8NtBg10el0er2e\n4zjhb+wKf+9Q2AGIjERGUg/SFViOYiuWuR49eqxcuXL69Ok7duwoWy2p1eqJEyd+/fXX9erV\nq+xIi+bOnavVatu3b3/q1CmVSmV6cejQoX369OnYsePNmzfnz59/4sQJIpozZ86cOXPKf4Vm\nzZpNmjRp6dKl+/fvNxqN5iokICBgyZIl5mHvvvsuEXl6elbtf4g1SktLi4qK7DoFEWk0GlNh\np1ar7VoJmRZpPDw87F0JmQo7lUpl17KbiHJyclQqlfnbzE5yc3MNBoNcLler1XadqKioSK/X\nV/z91usl4insiMjt/C/U+yXhWYqKijiOE56owioWhycAxEfgYCxW7Bxh2rRpcXFxw4cP9/X1\nlcvljRo1Gj9+/OXLl+VyORG1aNGiCiOfkJeXl5CQQERTpkx54p9btVr9xhtvEFF8fHyFe2cd\nO3YkouLi4rK9UQCAiKjrYFK68UZP7yYdi912rNgBiI/Sm4rvWg5hxc5BgoODg4ODn3gxNjaW\niPr161e1kWWZW5w0bNiwfLRp06ZEpNfri4uLhVcLTPUcx3H2XiMBqHnc1NS5H53aZTlakEMX\njtBzz1uO2g5W7ADER+hWMRR2rLVp04bjuM8+++yJ169evZqUlMRxnLlcs35keXXq1DF98Ntv\nv5WPmsq+WrVqeXp63r9/n+M4juOOHDlSfmR8fDwRtW3b1rRGCAB/4wSdilHYAYiP0K1iKOxY\nMx0v3blzp7HMiRaDwWB6Um3IkCH169ev7MjyfHx8TJ2Nv/jii6Kivx3c02g0GzZsICLTqVg/\nPz9TK+PPP//8iS9y+fJl0/VlY8eOrfobBnBh3YaQjP/ow6lo0tv9pDAKOwDxEWhlpyskA4tW\nCGA2adIkIjpz5sz48eNTUlI0Gk1iYuLgwYNjYmJUKtWnn35ahZEWffDBB0R069atfv36nThx\noqioKCcn58iRIz179kxMTFSpVO+//75p5KxZs4goOjp69OjRFy5cKC0tzc7O3rJly4ABA/R6\nfdOmTadOnWqn/xsANZvaizr15Y3mPaZLx+2dAgo7APHBrWLOJCIiwrTk9t1337Vo0UKpVHbu\n3DkmJkahUGzatKl169ZVGElE7dq14ziuW7du5lciIyNXr14tl8vj4+PDw8M9PDxMbUrOnDmj\nUqk2bdpkvlJsypQpb731FhFt3bq1U6dOKpXKx8fnH//4R0ZGhp+f3+7du+19HBWgBgsV3I09\naffdWBR2AOKDyyeczGeffbZjx46IiAgfHx+ZTObn5zd27NjExMTIyMgqj7ToX//6V1JS0tSp\nUwMDA03dKFq0aDFlypTLly+X/Qocx61Zs+bo0aMvvvhi/fr1ZTKZt7d3ly5dPvrooxs3brRv\n396Wbx7AxXQfSlL+k6nxO8lg33bKOBULID7ChR1W7Bxh+PDhw4cPt+HIK1euWHw9MDCw/MNz\nFvXq1ct8eywAWKtWHerQixIPWY5mZ1JSLHWw458srNgBiE8FW7FYsQMAqAbh3di96+w6OQo7\nAPERvi4WW7EAANXRYxhJ+C8RObmDHqXbb3IUdgDiI3MnCf+BfGzFAgBUh3d9ah/KG9XraPcX\n9pschR2AKKFHMQCA/fR7TSga8w2VFttpZhR2AKIkcH4ChR0AQDX1Gk0+frzR3Ed0dJOdZkZh\nByBKAoUdtmIBAKpJpqBBk4UG7IyiMlfI2BAKOwBRwq1iAAB2NeSfJFfyRm9docvH7TEtCjsA\nURJ6xi6XyC4/RwIAiIiXL4WNFBqwc7U9pkVhByBKAluxRj3pChimAgDgoiKnC0VP76aMVJvP\nicIOQJSEexTj/AQAQPW17ExtuvNGjQbaY/u+JyjsAEQJ18UCADAwbJpQdP96KrbxDgkKOwBR\nwnWxAAAMhI6guo14owU5dPg7206Iwg5AlCq4VSybVR4AAC5NKqPBU4QG7Iwio8GGE6KwAxAl\neS3i+P/4Y8UOAMBWBk0mpRtvNP03On/IhrOhsAMQJU5CMk/eKAo7AABbqV2XwscIDYi2Zd8T\nFHYAYiXwmF0ptmIBAGznxRnE/X97dx5WVZ3/AfxzFy4gi2wiE6JQKou4oGiL6Oi4pWU6aIrL\njNbUM9kyNZlaD6VSVD5a41MmlmNTZopaglJOmKSmUS7TyLhhoZJgKCiyisBdzu+P72/uc+du\nHC73nnvu975ff/TIOefe831zzvn0ucv5orC59sRXVHneWbtCYwfgrezMeIJ37AAAnCg2mQaO\ntrlWEJw47wkaOwBvhT8XCwAgGfvznuz7WNHS6JT9oLED8FZ2GjvcFQsA4Fz3TaOoOJtrbzep\nnDTvCRo7AG+ltv1RrL6VDG0SDgUAgHdKFU1dZGe9z94NZNA7YT9dfwoA8EiYoxgAQEqTHye/\nAFsrFdW/aEqKur4TNHYA3sp+Y4cbYwEAnCswhMb/wc56/31/7/pO0NgBeCs7d8US3rEDAHCB\n6X+xM++Jz+lvVZfPdnEPaOwAvJVvqL217fVSjQMAwGv0TqSU8XbW++3/Rxf3gMYOwFvZf8cO\njR0AgCv83t68J5rDO6ixtitPj8YOwFspfUnlZ3OtDh/FAgC4wIgHqFe8rZWK9ttU+GFXnh6N\nHYAXszeVHd6xAwBwAYXC/rwnVLCe9DqHnx6NHYAX80FjBwAgufsfpQDbX4apqaDv9zj83Gjs\nALwY/lwsAID0/INowgJ7G+x+1+Hndk9jV1tb+8orr6SkpISFhfn6+kZHR6enp+/fv99ss8OH\nDytsu3btmlsGD8APOzfG4h07AADXmf4MKWz3YKcP08//cuyJ3dDYlZSUJCUlZWdnl5SU1NXV\ntbe3V1VV5efnT5w48eWXXzbd8tKlS9IPD8CL2HvHrpEEJ/xxGwAAsOKOvjRisr0Nvshx7Iml\nbuy0Wm16enpNTU2vXr127NhRW1vb2Nh45MiRkSNHEtHrr79eUFBg3PjixYtEtG7dOsGaqKgo\niQcPwBt7M54IpG2SbiQAAN5mur15T6i2igTBgWeVurHbvXt3eXm5Wq3ev3//rFmzwsLCgoKC\n0tLS9u/f379/fyJ67bXXjBuzxq5fv34SDxLAW2jszlGsxaexAAAuM2wixQ00X+jjS+P/QO+X\n0BuFdv5GhR1qJ4ysMw4cOEBEY8aMSUhIMF3u7+8/d+7clStX/vjjj83NzYGBgfTfxo41fC51\nuV7/5c+tXX8enU5PRGr1ra4/VadotQaDQalUGnx8pN61eyOrVAbpd81V5PY4anrS5tpDP5Oi\njIgEg0BECqUjJaYrDAZhSA8aknSvxPsFAJDI1Cfp3f+f+kQI7Xn7d39sm/RYaGyX2h6pG7uK\nigoiSkxMtFwVHR1NRIIgmDZ2Go2md+/erh6VXhBadY684WlGpxOISE1OeKrO7VdPBgMpBdIr\nJN+1myMLbtg1T5EFDQm25yj+734EwUBECkHqN/gFwaAXHJ/MCQBA7ib8kT7KpKg4mv6X23dP\na2nXKpVdrbRSN3Z79+61terQoUNEFBwc3KNHDyJqbGysra1NTEzMy8tbv359SUlJa2trTEzM\n5MmTlyxZEhMTI9mYAbil9HH3CAAAvJhvN/r7GQr7DRFRSwu1a7v+lFI3drbk5ubm5uYS0bx5\n81QqFf33c9iffvpp1qxZxs0uXLiwbt26zZs35+bmTpkyxfQZrl+/fuTIEeOPLS0tvr6+ra2i\nPmBtbzcYDAanBCEiJz6VSIIgsP9Kv2sGkSXgksgC+waHqLcABcnfpGT0er2YC1mvxz28AOCB\nWFfnPO5v7Nra2lasWLF69WpBEPr165ednc2Ws8bOYDAMHjx4zZo19913X2tr6969e5ctW3bt\n2rWZM2ceP348OTnZ+DwVFRVvvPGG8cfExMSwkQIsnwAAIABJREFUsLDm5mYxY2hpIZ3OaR8z\nuavVEARBp3PP51aILBmnR1aTigziXiM6dH9W1+l0OjEXMho7AABye2P37bffLlq0qLS0lIjS\n0tI+++yzsLAwtoo1diNGjDh48GC3bt2IKCAg4I9//OOoUaOGDh1aX1+/fPnyvLw841OpVKrg\n4GDjj+xTaoW4O0ocuu8EgAeCUqMQ2di5icirGAAAyI2NXW1t7eLFizdv3kxE3bp1y8rK+utf\n/8o+hGWWLVu2bNkyywfGxcU9/vjja9asKSwsFATBWPSHDBnCbrlllixZQkTh4eFiBtOg1Gk0\nTrkrVkdEarXUv1WdTsdui3XLrgmRpdqvSyLrQslw2/4m/3/zhJ1J0l2D7Vej0QQFBXW4sUaj\ncf2IAADkzj2N3ZEjR2bPnn316lUimjVr1po1azp162tKSgoR3b59u76+PjTU7kRcAGCff09q\nu0GGdnePAwAAnMANjd3BgwcnT57c1tYWGxu7adOmcePGdfYZ6uvriUihULBZUQDAcQo1BcdT\n0wXSd/C+HQAAyJ/UjV1jY+OcOXPa2tqGDx9eWFho/EadmWvXrv3mN78hoqKiIsvOr7i4mIgG\nDBjg4+OcyRpC/JQjejnhc5zWVgMR+flJ/ZHQ7dt6nU5QqxX+/lLv2r2RfXyU0u+ax8gaEoZQ\ny2VqrbF6I4VWqyMiZ11u4rVrdT264y15AIBOkLqx27x5c3V1dWRkZEFBga2ujoiioqLuuuuu\nixcvvvfee2aN3alTp7Zv305E8+bNc9aowvyVo3o74X+Wzc3tRBQYKPX/8hsbW9vbBY1GERws\n9a7dG9nXVxEUhMjOEk8Ub3UFuylV+jfIGxsb29vxGTEAQCdI/W3oHTt2ENGiRYuioqLsb7l4\n8WIi2r17d0ZGxsmTJ9va2urq6nJzc++//369Xh8bG/vUU09JMWIAAAAADyFpY6fX60+cOEFE\nWVlZCtvYZKRPPPHE008/TUQ7duwYOnSon59fWFjY3Llzr169GhUVVVBQIOZGOQAAAADvIWlj\nd/nyZfEfrCgUinXr1h04cGDGjBk9e/ZUq9WhoaEjRox49dVXz58/P3DgQJcOFQAAAMDjSPod\nuzvvvFPo5OT1Y8eOHTt2rIvGAwAAAMATqb9jBwAAAAAugsYOAAAAgBNo7AAAAAA4gcYOAAAA\ngBNo7AAAAAA4gcYOAAAAgBNo7AAAAAA4gcYOAAAAgBNo7AAAAAA4gcYOAAAAgBNo7AAAAAA4\ngcYOAAAAgBNo7AAAAAA4gcYOAAAAgBNo7AAAAAA4gcYOAAAAgBNqdw/Ahc6ePfviiy9KuUed\nTkdEarXUv1WtVmswGJRKpY+Pj8S7dm9klUol/a4RWTKdinz27FkJhgQiubr8GgwGnU6n0Whc\ntwu2F61WS0QajUahULh0X21tbdLshYh8fHyUSte+raPVapVKpUqlcvVepKmKer1eEAQJ9qLT\n6RQKhf0Tu8Nax3NjV1NTU1RU5O5RAIB0pH9tA1ah/AK4lJ1ax21jN2XKlOTkZHePQiL//Oc/\nL168eNddd02ZMsXdY5HI3r17L1265FWRv/zyy/Ly8r59+06ePNndY5EIi9yvX7/7779f5EPu\nvfdelw4JxOCm/F6+fLmgoICIHnvsMX9/f3cPp6sMBsP69euJaNKkSf3793f3cJwgPz//ypUr\nSUlJ48aNc/dYnODEiRNHjx4NDAx85JFHOtzYTq3jtrEbO3asu4cgnTNnzly8eLF3794LFixw\n91gkcurUqUuXLvXp08d7Iv/nP/8pLy+PjY31nsglJSXeFpkP3JTf4uJi1thlZGSEhIS4ezhd\npdPpWGM3evToSZMmuXs4TvDDDz9cuXKlb9++fJQIvV5/9OjRbt26dTEObp4AAAAA4AQaOwAA\nAABOKARBcPcYoKtaWlp0Op1are7WrZu7xyIRFtnHx4eDL76IhMgAEtPpdC0tLUQUFBTk6vtV\npdHY2EhE/v7+fNxmxFmJaG9vb21tVSqVgYGBXXkeNHYAAAAAnMBHsQAAAACcQGMHAAAAwAk0\ndgAAAACcQGMHAAAAwAk0dgAAAACcQGMHAAAAwAk0dgAAAACcQGMHAAAAwAk0dgAAAACcULt7\nAN7l1q1b33zzTWlpqUajSUtLGz58uLtH5HKIjMgAEuDsJEQcmZN1IgEk0dTUlJmZGRwcbPrL\nnzhxYnV1tbuH5iqIjMgAEuDsJEQcmZN/IjR2Ujh69GhcXBw7/Gq1evjw4WlpaexvMCcmJjY0\nNLh7gM6HyIjMZWSQG85OQsSROY9IhMbO5bZv3+7r68vOg4ULF1ZUVLDl5eXlycnJRDR//nz3\njtDpEBmRuYwMcsPZSYg4MucpidDYudaWLVuUSiURBQUF5efnm629cOGCWq1WqVSXL192y/Bc\nAZHN1iIygCtwdhIijsx5UCI0di60b98+tVpNRJGRkSdPnrS6zYgRI4ho165dEo/NRRDZ6jaI\nDOBcnJ2EiCNznpUId8W6yq+//jp37lydThcREXHw4MGkpCSrm9XV1RFRW1ubtKNzCURGZCOe\nIoPccHYSIo7MeV4id3eW3EpPTycijUZTXFxsa5sjR46wo1BSUiLl2FwEka1CZADn4uwkRByZ\n87hEaOxcoqSkhB3jVatW2dpGq9UOGzaMiOLj46Ucm4sgslWIDOBcnJ2EiCNznpgIjZ1LLF26\nlIh69erV1tZma5vFixez0yU3N1fKsbkIIluFyADOxdlJiDgy54mJ0Ni5xMSJE4lo8eLFtjbI\nyclh58HUqVOlHJjrILIlRAZwOs5OQsSROU9MhL8V6xI6nY6IevXqZXXthg0bnnrqKSLq37//\n5s2bJR2ZyyCyGUSWdGTgNTg7CRFH5jwxERo7lxg0aBARGb9NaWQwGJYvX/7kk08KghATE/P1\n11+Hhoa6Y4DOh8hGiMxTZJAbzk5CxJE5j0zkvjcLeVZaWsrmvMnJyTEuLCsrmzBhAvu1x8fH\ny2EaQydCZAaROYsMcsPZSYg4MueJiRSCILiua/Rm77333jPPPENEKSkpKSkpFRUVhw4dYm/q\nTp8+/eOPP+7evbv9Z7h169Y333xTWlqq0WjS0tKGDx8uxbi7AJERmcvIIDecnYSIY0ZWcajL\nidwQx92dJc+2bNkSGBho+ttOSEjYuXNnhw9samrKzMwMDg42fezEiROrq6slGHZXIDIi2+G5\nkUFuODsJEYeRZxzB0UTuioN37FyrqakpPz+/srIyICBg5MiRqampCoXC/kOOHTs2Z86c8vJy\nIlKr1SkpKb6+vseOHdNqtYmJiUePHjU7S+QGkRHZKk+PDHLD2UmIOHKOQ51P5M44Lm0bobO2\nb9/u6+vLDs3ChQsrKirY8vLy8uTkZCKaP3++e0fodIiMyFxGBrnh7CREHDlzbxw0djKyZcsW\npVJJREFBQfn5+WZrL1y4oFarVSqV3L6n2RWIbLYWkQFcgbOTEHHkzO1x0NhJbe3atVu3brVc\nvm/fPnbrTWRk5MmTJ60+dsSIEUS0a9cuF4/RyRDZCJGtPtZDI4PccHYSIo6RDOMINhLJIQ4a\nO0n98MMPRKRSqczOhitXroSHhxNRRETE2bNnbT28X79+RLRt2zbXj9RpENkIkW093BMjg9xw\ndhIijim5xRFsJJJJHDR2UluxYoWvr29hYaHpwvT0dCLSaDTFxcW2HmicILGkpMT1w3QmRGYQ\n2SrPjQxyw9lJiDiMPOMI1hLJJA4aOze4cOGC6Y8lJSXsMK9atcrWQ7Ra7bBhw4goPj7e9QN0\nPkRGZKs8PTLIDWcnIeLIOY7wv4nkEweNnfstXbqUiHr16tXW1mZrm8WLF7MzJjc3V8qxuQgi\nW4XIAM7F2UmIOHImnzhqAndjbf7s2bM1Go3VDTZs2PD2228T0dSpUzMyMthCuc3N3SmIbAmR\n2UKPjgxyw9lJiDiEOGK4rmcEkX73u98R0dq1a62uzcnJYbMg9u/f/+bNm4KM5+YWD5HNILLA\nRWSQG85OQsRBHDHQ2Lnfc889R0Tp6elmy/V6/SuvvMIOdkxMzC+//CIIwtGjR+Pi4thCtVo9\nfPjwtLQ0Hx8fIkpMTGxoaHBHgk5DZCNE5ikyyA1nJyHiII4YaOzcr7S0lE17k5OTY1xYVlY2\nYcIEdtTj4+PZTIbczM2NyAwicxYZ5IazkxBxEEcMNHaysG7dOnaMU1JSHn300fHjx7Pzg4im\nT59eX18vyGAya+dCZETmMjLIDWcnIeKYPQPiWEJjJxdbtmwJDAwkEwkJCTt37mRr5TCZtdMh\nMiJzGRnkhrOTEHHMII4Z3BUrF/Pnz582bVp+fn5lZWVAQMDIkSNTU1PZdy1//fXXuXPn6nS6\niIiIgwcPJiUlWX2Guro6Impra5N03F2AyIjMZWSQG85OQsQxgzjmHG4JQTIymcxaSohsFSID\nOBdnJyHiyJlkcdDYyZ18JrOWDCJbhcgAzsXZSYg4ciZlHDR2ciefyawlg8hWITKAc3F2EiKO\nnEkZB9+xkzsZTWYtFUS2hMhsoUdHBrlx4CSU8xnI2TWFOORwnK50hSAB+UxmLRlENoPIAheR\nQW46dRLK/wzk7JpCHIfjoLGTO/lMZi0ZRDZCZJ4ig9yIPwk94gzk7JpCHIfjoLGTO/lMZi0Z\nRGYQmbPIIDciT0JPOQM5u6YQx+E4aOw8gEwms5YSIiMyl5FBbjo8CT3rDOTsmkIcs2cQGQeN\nnWeQw2TWEkNkROYyMsiNnZPQE89Azq4pxDEjJg7uivUMspjMWlqIjMhcRga5sXUSeugZyNk1\nhThmRMVxfkcK0uJsbm4xENkqRAZwIv7OQM4SIY4taOw8G2dzc4uByFYhMoAT8XcGcpYIcexA\nY+fZOJubWwxEtgqRAZyIvzOQs0SIYwe+Y+fZOJubWwzHIns0RLZkNfJPP/20c+fO8vLyyMjI\nBx98MC0tTbIBA2f4K62clRHEITsVz9l9J0iKs7m5xehsZKa0tHTOnDk3btyQapjOhMhmLCNr\ntdrnn3+eTRNgNHXq1Lq6OmkHDpzgr7RyVka8PI79iofGzrNxNje3GJ2KbFzF7jCKjo7Oy8sz\nGAwtLS2bNm26cuWKtGN3ECIb2Yq8efNmtjA6Ovqxxx6bOXOmn58fESUkJNTU1Eg+fPB4/JVW\nzsqIl8exX/HQ2Hk2zubmFkN8ZFM//vhjaGgo2yAkJIT9KpKSkrRarbTDdwQiM/YjL1u27Omn\nnzZ+Q6W8vHzgwIFENHLkSL1eL+nowfPxV1o5KyOIY6fiobHzeJzNzS2GmMiWTC9pItJoNHv2\n7JF45A5DZJGRTVVVVbH4H330kevHC7zhr7RyVkYQx4yx4qGx4wFnc3OLYT+ynUfJ7WIWD5FF\nRjb19NNPE9GECRNcN0jgGH+llbMygjhmWMVTCIJA4PmamppsTWY9ePDg2traiIiIb7/91tZk\n1v379y8rK9u2bducOXOkHbjjbEW25fTp0+PGjbt+/bpGo/nss88eeughyYbqLIjcYWQz2dnZ\nr7zySmJi4rlz51w3SOAYf6WVszLi5XHMsIqHd+w4x9nc3A47depUjx49SH4v0VzHCyNbGjVq\nFOEdO3ABLymtnJURzuJYYhUPjR3POJub22HcX8yWOI5sMBh27979wAMP3HHHHSEhIf369Zsx\nY8bbb7994sQJnU5n3Eyv1y9fvpyd/++8844bBwz88ZLSylkZ8dA4DlQ8NHY868pk1u3t7VlZ\nWXK4D7yLPPRi7grxkT3uKJ8+fXrIkCG2Pobo1q3bvffeu2DBgkceeSQxMZEt7Nu3b0tLi7sH\nDlzxhtLKWeX00KroWMVDY8eziRMnEtHixYttbZCTk8NOhalTp5our6iouPfee9kpIpPz2zEi\nL+bm5uY9e/asWrXqb3/72/Hjx6UcodOJr18ed5TPnj3r7+9PRH5+fo8//vjnn39+6NChXbt2\nLV++/Le//a3VGdv79u37888/u3vgwBvuSytnldNDq6LDFQ+NHc8cm5v7q6++Cg8PJyJ2w5cc\nzm/HiLmY5T9ffKeIr18eepRXrFhBRCqVauvWrWarbt26VVRU9Prrr8+dO3f8+PEzZsxYv349\ne6+OHWV3jBf4xHdp5axyenRVdKziobHjWWcns9bpdJmZmawkLVy4sLKyMiUlRSbnd2eJuZg9\nYr548UTWL08/ynYqnVXGo+zqgYH34Li0clY5OaiKDlQ8FDuedWoy66tXr44ZM4aIAgMDt2zZ\nwhbW1tbK5/wWT8zF7CnzxYsksn7xcZTFVzrToyzN2MAb8FpaOauc3FTFTlc8aYYF7iJyMusD\nBw5ERUUR0cCBA8+fP2/6DLI6v8Worq7u8GL2rPniOyQmssDXURZT6ewfZYCu4K+0clY5OauK\nnap4aOz41+Fk1tXV1d27d2erNBrNmDFjDh48aPoMpud3bW2t1AE6b8WKFXYuZk+cL75D9iML\nnB5lO5VOzFEG6Ar+SitnlZOzqii+4qGx8wqNjY2bN2/Ozs5eu3bt8ePHDQaD2QaHDx+eMmXK\n1KlTo6OjiUipVJpN/cXO70WLFlk+Vp5++uknq8uvXLnCvh4bERFx9uxZWw/v168fEW3bts1l\nA3Q+W5GN+DvKtiqdyKMM0EX8lVbOKidnVVFkxUNj572Ki4tfeOEFs4UGg2Ht2rUKhUKhUJi9\n0GlsbJTDmd1FXjJfvBH3R9lY6Uw/GBJzlAFchMuLjqfK6dEHSEzFQ2PnvYYOHUpEr776quWq\nl156iYhiY2P1er30A3MdL5kv3pQ3HOUVK1YkJCRcvXqV/SjmKAO4Dn8XHWeV09MPUIcVD42d\nlyorK2OnwhdffGG59vr16+zGb87e8OjKfPGeyHuOclNTk/HfYo4ygItwedHxVDn5OED2K56S\nwCtdvXqViBQKxf3332+5NiIiIjQ0lIjOnz8v9chcib2ymT17ttU5u4low4YNb7/9NhFNnTo1\nIyND0sG5gPccZdPvsHd4lAFch8uLjqfKyccBsl/x0Nh5qdjYWCISBKG2ttZybV1dXUNDA/13\nAm5u6HQ6IurVq5fVtRs2bHjqqaeIqH///ps3b5Z0ZK6BowwgMS4vOp4qJ38HyPLooLHzUjEx\nMampqUT01ltvWa5dtWqVXq8nouHDh0s9MlcaNGgQERm/4WtkMBiWL1/+5JNPCoIQExPz9ddf\nsxdtng5HGUBiXF50PFVO/g6QlaMj+UfDIBdff/01ESkUio0bNxoX6vX67Oxs9iWDSZMmuXF4\nrtCp+eL5gKPMlJWVuXFI4FX4u+g4q5ycHSDLo4PGzqutWrWKXZYTJkx46623li1blpCQwJb0\n7t27qqrK3QN0PpHzxfMER5kdZXcPCrwIfxcdZ5WTswNkdnTQ2Hm7f/zjHwEBAWZv7Y4dO9bj\nzmzxOpwvnj84yvh0AiTG30XHWeXk7ACZHh2FIAgE3q2qqionJ+fIkSM6nW7AgAEPP/yw8Q12\nXjU1NeXn51dWVgYEBIwcOTI1NZW9A88xHGUP+tIM8IG/i46zysnZATIeHTR2AAAAAJzAXbEA\nAAAAnEBjBwAAAMAJNHYAAAAAnEBjBwAAAMAJNHYAAAAAnEBjx4MnnnhCIdqhQ4eI6NNPP1Uo\nFLL6e5quGNKXX36pUCjM5l6yZf78+QqF4uWXX3biADrUqRECgLOgbNqCsunp0NgBAAAAcAKN\nHQ/ef/99s0mojX9g5OrVq2arxowZ49bBAgC4H8om8AqNHQAAAAAn0NgB5ebmjhw5MiQkJCgo\nKDU19YMPPjBdy77NkJycLAjCxo0bBwwY4OPjU1JSwtbq9fpNmzaNHj06NDQ0ICBg8ODB2dnZ\nDQ0NZrvQ6/Xr16+/5557goODfX19Y2JiMjIyjh8/7tiQmMbGxpUrVw4ZMiQoKCgwMHDIkCEr\nV66sr68XE/ncuXPz5s274447/Pz84uLiFi9efPPmzQ4fNX36dIVC0bt3b8tVZWVl7Ls4X331\nlXHhyZMnn3jiicTExMDAwPDw8MGDBz///PMXL160v5f333/f1pdmIiIiFArF559/brpQ5CEA\nACdC2UTZlC/n/QlakBE7nykwW7ZsIaLo6OgXXnjB8qxYsmSJccsvvviCiAYMGPDoo48aNzh5\n8qQgCPX19aNHj7Z8eHR09L/+9S/jM7S3t1v9A3xKpfKTTz5xYEiCIJw9e9bqNWy2azb4gIAA\n08cWFhb6+vqaPTAxMXHy5MlElJmZaeu3umPHDrax6S6YN954g4giIyO1Wi1bkpOTY/WvKGo0\nmry8PDsj3LBhAwtiOYDw8HAi+uyzz4xLRB4CAOgQyqbp4FE2PRcaOz6JrFDsEpo2bdqJEyda\nWlrKysqmTJnCase1a9fYluwSUqlURLRo0aKLFy/q9XpBEAwGA7uku3fv/uGHH968ebOpqWn/\n/v3JyclE1LNnz9raWvYM7777LhGFhYXt3r27vr6+ra3t9OnT8+fPJ6Lg4GDjZuKHVF9f36dP\nH1ZWCgsLm5ub6+vr9+7dm5iYyMpEVVWV6eBNr/9r1651796diBISEgoLC1taWqqrq1evXu3j\n48N+Y3YqVEtLS1BQEBG9/PLLZquGDh1KRM888wz7sampqVu3bkQ0Z86cc+fOtbe3NzQ0fP/9\n9+PGjWMj1Ol0tkYovkKJPwQA0CGUTdPBo2x6LjR2fBJZoYhowYIFpstv3LihVquJ6NNPP2VL\n2CVERLNmzTLdMi8vjy0/ePCg6fKampqIiAgiysrKYksmTpxIREuXLjXdTKfTxcbGEtEXX3zR\n2SGxW+u7d+9ulq6mpiYyMpKInn32WdPBm17/zz33HBFFRUVdv37d9LF///vfO6xQgiD84Q9/\nICL2CYtReXk5e+yxY8fYksOHDxNReHh4e3u76ZaXL19mW5aXl9saofgKJf4QAECHUDZNB4+y\n6bnwHTtvt2TJEtMfw8PDWeGoqqoy2zIzM9P0x40bNxLRtGnTzO4X69Gjx4IFC4ho7969bElr\naysRHTx4sKWlxbiZSqViV+mDDz7Y2SF9/PHHRPTII49ERUWZ7XrhwoVEZLx0zQiCsHXrViJ6\n/vnn2TVs9Oijj4qZC2ru3LlEdObMGdPvfLBvb/Tr12/EiBFsyahRowRBuHHjhvEVLVNZWcn+\nwX4nXST+EACAE6FsMiib8oTGzqv5+fklJSWZLQwODiaixsZG04Vqtdp0S0EQiouLiSgtLc3y\nae+77z4iOnXqFPtx+vTpRHTixImEhISlS5cWFhY2NTU5PKTKysorV64Q0YwZMywfPmrUKLZN\nXV2d5dqysrLr168TEXtv35RSqWTDtm/ChAns1e3u3buNC3ft2kVE8+bNs9z+8uXL27dvf+ON\nNx577LGxY8eOHz++w12I1KlDAADOgrJphLIpT2jsvFpISIjlN1XZEkEQTBf6+vqyN/aZhoYG\nVmWWLFliOUs7qx2tra23bt0iomefffbFF1/09fWtrKxcs2bN5MmTw8LCRo0a9c4775jVQTFD\nMr4AZa9HzfTo0YP9w2qFYqWNiKKjoy3Xmr2QtUqlUj388MNkUqGuXLly7NgxsqhQ33//fUpK\nSmxs7Jw5czIzMz/88MNDhw4NGjSow12I1KlDAADOgrJpCmVThtDYeTX23V4HaLVaMZu1tbUR\nkVKpfPPNNysqKjZu3Jienh4REaHT6b777rvnnnsuOTn5l19+6dSQ2HMSEfuarRnj/er+/v6W\na/V6PftHe3u75VqdTmd/1wz7WOH7779nr2LZvVr33HNP3759jdscOHBg9OjRJSUlwcHBGRkZ\nq1ev3rNnz6+//rpnzx4xu7ClubnZ+O9OHQIAcBaUTVMomzKExg4cERISolQqieijjz6y8xXO\nsLAw40MiIyMff/zxXbt21dTU/Pvf/87MzNRoNJWVlVlZWZ3atfE5jd+oNcUW+vn5GV+DmmLf\noiWiiooKy7XGF6b23XfffXFxcQaDoaCggP77TRGz150rV67U6/WDBg0qLy/Pzc1dsmTJQw89\ndMcdd4gsK1Y1NDSYlhsHDgEAuBHKJsqmNNDYgSN8fHzY2+MnT560XJuVlaVQKNiXGCoqKti7\n3MYXhQqFIiUlJTs7e9myZUR0+vTpTu06Pj6evawsKiqyXMte26Wmppp+AmI0YMAANhXTvn37\nzFZptdrvvvtO5BgyMjKIaPfu3dXV1cXFxWq1evbs2aYbsF/Ln//8Z7MCcf78+Q6fXKPRENHt\n27fNlrOvhhiJPwQAIAcom4SyKQk0duAgdpV+9NFHNTU1psurqqrYDEzsFveYmBjLr80y7LsO\nZrdZdcjHx2fatGlE9M4775h9m/jnn39mpYfd3GTJ19eXfSX5gw8+MJtk/N133xUzizrDXmgW\nFRVt2bLFYDBMmjTJ7JUuu6vrxo0bpgvb29tfffXVDp+8Z8+eRHTz5k3TO8gEQVi7dq3ZliIP\nAQDIBMomyqYU7LwbCZ5L/BTqlquGDRtGJvMSWZ2FXBCExsZG9vWIIUOGFBUV3bp1q7m5uaCg\n4K677iKiAQMGGOcievHFF4koMDDw/fffv3r1ant7+6VLl1577TX26tD4lrj4IZ07d87Pz4+I\n7r777m+//balpaWhoaGgoCAuLs5s15aDLy0tZa9chw8ffvjw4ZaWlpqamjfffFOlUrGbyOxP\nyGQ0cOBAImITb27bts1sbXp6Olu7c+fO5ubm6urq3NzcQYMGaTQa9kHA/v372SAtR1hXV8de\nfaalpZWWlra2tp45c2bWrFnsd0gmEzKJPwQA0CGUTVuDR9n0LGjs+CRBhRIE4fz586womElI\nSLh48aJxs+bm5pSUFKuvKzIyMgwGQ2eHJAhCXl6e5d+3IaI+ffqY7trq4PPy8lgJMDV69OiX\nXnpJfIV688032QMDAwNv3bpl+ZsJCQkx20VISMiXX345ePBg9uO8efNsjXD58uWW0ZYvX37P\nPffQ//5tHJGHAAA6hLJpZ/Aomx4EH8W91smCAAABXElEQVSC4+Lj40tKSlasWJGUlOTn5xce\nHj5ixIjVq1efOHHizjvvNG4WEBBw+PDh7OzsYcOGBQUFqVSq8PDwcePGffLJJ9u2bbP6lwE7\n9Pvf//706dN/+tOf+vTpo9FoQkJCUlNTs7Ozz5w5Y7prW4/98ccfZ86cGRYW5u/vn5ycvGrV\nqqKiIsuyZcfcuXPZyNPT0y1vNIuPjz927NjMmTNDQ0P9/f3j4+OXLl167ty5Bx544L333rvz\nzjt9fHyszh3AZGVlbdq0KTU1NSAgwN/f/+677966dWtWVpbx9jTTHYk5BAAgEyibhLLpYgrh\nf+fdAQAAAAAPhXfsAAAAADiBxg4AAACAE2jsAAAAADiBxg4AAACAE2jsAAAAADiBxg4AAACA\nE2jsAAAAADiBxg4AAACAE2jsAAAAADiBxg4AAACAE2jsAAAAADiBxg4AAACAE2jsAAAAADjx\nf7qct77VUaUwAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot.threshold(ws.threshold1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "OK, so the results argue that a WS threshold of 1.7e-4 yields the appropriate number of taxa in the even positive control for library 1. However, there's a good argument to be made for calling ASVs and filtering contaminants on a run specific basis (to do that, each run should be its own phyloseq object at this stage, but let's move forward to stay illustrative). To that end, let's look at one of the positive controls from the second run. <br> \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Estimating filtering statistics from WS thresholds 1e-05 to 7e-04 by 1e-05\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A df[,5]: 70 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>threshold.value</th><th scope=col>control.taxa.count</th><th scope=col>control.taxa.matches</th><th scope=col>read.count</th><th scope=col>read.percent</th></tr>\n",
       "\t<tr><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.00001</td><td>32</td><td>25</td><td>13698507</td><td>99.99951</td></tr>\n",
       "\t<tr><td>0.00002</td><td>32</td><td>25</td><td>13698047</td><td>99.99615</td></tr>\n",
       "\t<tr><td>0.00003</td><td>29</td><td>25</td><td>13697298</td><td>99.99069</td></tr>\n",
       "\t<tr><td>0.00004</td><td>29</td><td>25</td><td>13696500</td><td>99.98486</td></tr>\n",
       "\t<tr><td>0.00005</td><td>29</td><td>25</td><td>13695537</td><td>99.97783</td></tr>\n",
       "\t<tr><td>0.00006</td><td>29</td><td>25</td><td>13694424</td><td>99.96970</td></tr>\n",
       "\t<tr><td>0.00007</td><td>29</td><td>25</td><td>13693231</td><td>99.96100</td></tr>\n",
       "\t<tr><td>0.00008</td><td>28</td><td>25</td><td>13692359</td><td>99.95463</td></tr>\n",
       "\t<tr><td>0.00009</td><td>28</td><td>25</td><td>13691054</td><td>99.94510</td></tr>\n",
       "\t<tr><td>0.00010</td><td>28</td><td>25</td><td>13689760</td><td>99.93566</td></tr>\n",
       "\t<tr><td>0.00011</td><td>28</td><td>25</td><td>13688361</td><td>99.92544</td></tr>\n",
       "\t<tr><td>0.00012</td><td>28</td><td>25</td><td>13687044</td><td>99.91583</td></tr>\n",
       "\t<tr><td>0.00013</td><td>28</td><td>25</td><td>13685916</td><td>99.90760</td></tr>\n",
       "\t<tr><td>0.00014</td><td>28</td><td>25</td><td>13684498</td><td>99.89724</td></tr>\n",
       "\t<tr><td>0.00015</td><td>28</td><td>25</td><td>13683125</td><td>99.88722</td></tr>\n",
       "\t<tr><td>0.00016</td><td>28</td><td>25</td><td>13682026</td><td>99.87920</td></tr>\n",
       "\t<tr><td>0.00017</td><td>27</td><td>25</td><td>13680575</td><td>99.86861</td></tr>\n",
       "\t<tr><td>0.00018</td><td>27</td><td>25</td><td>13679073</td><td>99.85764</td></tr>\n",
       "\t<tr><td>0.00019</td><td>27</td><td>25</td><td>13677622</td><td>99.84705</td></tr>\n",
       "\t<tr><td>0.00020</td><td>27</td><td>25</td><td>13676524</td><td>99.83903</td></tr>\n",
       "\t<tr><td>0.00021</td><td>27</td><td>25</td><td>13675156</td><td>99.82905</td></tr>\n",
       "\t<tr><td>0.00022</td><td>27</td><td>25</td><td>13674016</td><td>99.82073</td></tr>\n",
       "\t<tr><td>0.00023</td><td>27</td><td>25</td><td>13673039</td><td>99.81359</td></tr>\n",
       "\t<tr><td>0.00024</td><td>27</td><td>25</td><td>13671602</td><td>99.80310</td></tr>\n",
       "\t<tr><td>0.00025</td><td>27</td><td>25</td><td>13670326</td><td>99.79379</td></tr>\n",
       "\t<tr><td>0.00026</td><td>27</td><td>25</td><td>13668995</td><td>99.78407</td></tr>\n",
       "\t<tr><td>0.00027</td><td>27</td><td>25</td><td>13667588</td><td>99.77380</td></tr>\n",
       "\t<tr><td>0.00028</td><td>27</td><td>25</td><td>13665666</td><td>99.75977</td></tr>\n",
       "\t<tr><td>0.00029</td><td>27</td><td>25</td><td>13664530</td><td>99.75148</td></tr>\n",
       "\t<tr><td>0.00030</td><td>27</td><td>25</td><td>13663359</td><td>99.74293</td></tr>\n",
       "\t<tr><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr>\n",
       "\t<tr><td>0.00041</td><td>26</td><td>25</td><td>13648667</td><td>99.63568</td></tr>\n",
       "\t<tr><td>0.00042</td><td>26</td><td>25</td><td>13647442</td><td>99.62673</td></tr>\n",
       "\t<tr><td>0.00043</td><td>26</td><td>25</td><td>13646378</td><td>99.61897</td></tr>\n",
       "\t<tr><td>0.00044</td><td>26</td><td>25</td><td>13645423</td><td>99.61200</td></tr>\n",
       "\t<tr><td>0.00045</td><td>26</td><td>25</td><td>13644717</td><td>99.60684</td></tr>\n",
       "\t<tr><td>0.00046</td><td>26</td><td>25</td><td>13643418</td><td>99.59736</td></tr>\n",
       "\t<tr><td>0.00047</td><td>26</td><td>25</td><td>13642649</td><td>99.59175</td></tr>\n",
       "\t<tr><td>0.00048</td><td>26</td><td>25</td><td>13641861</td><td>99.58599</td></tr>\n",
       "\t<tr><td>0.00049</td><td>26</td><td>25</td><td>13640887</td><td>99.57888</td></tr>\n",
       "\t<tr><td>0.00050</td><td>26</td><td>25</td><td>13639816</td><td>99.57106</td></tr>\n",
       "\t<tr><td>0.00051</td><td>26</td><td>25</td><td>13637863</td><td>99.55681</td></tr>\n",
       "\t<tr><td>0.00052</td><td>26</td><td>25</td><td>13637181</td><td>99.55183</td></tr>\n",
       "\t<tr><td>0.00053</td><td>26</td><td>25</td><td>13635759</td><td>99.54145</td></tr>\n",
       "\t<tr><td>0.00054</td><td>26</td><td>25</td><td>13634625</td><td>99.53317</td></tr>\n",
       "\t<tr><td>0.00055</td><td>26</td><td>25</td><td>13633344</td><td>99.52382</td></tr>\n",
       "\t<tr><td>0.00056</td><td>26</td><td>25</td><td>13632121</td><td>99.51489</td></tr>\n",
       "\t<tr><td>0.00057</td><td>26</td><td>25</td><td>13630886</td><td>99.50588</td></tr>\n",
       "\t<tr><td>0.00058</td><td>26</td><td>25</td><td>13629658</td><td>99.49691</td></tr>\n",
       "\t<tr><td>0.00059</td><td>26</td><td>25</td><td>13628585</td><td>99.48908</td></tr>\n",
       "\t<tr><td>0.00060</td><td>26</td><td>25</td><td>13627639</td><td>99.48217</td></tr>\n",
       "\t<tr><td>0.00061</td><td>26</td><td>25</td><td>13626268</td><td>99.47216</td></tr>\n",
       "\t<tr><td>0.00062</td><td>26</td><td>25</td><td>13625068</td><td>99.46340</td></tr>\n",
       "\t<tr><td>0.00063</td><td>26</td><td>25</td><td>13623688</td><td>99.45333</td></tr>\n",
       "\t<tr><td>0.00064</td><td>26</td><td>25</td><td>13621808</td><td>99.43961</td></tr>\n",
       "\t<tr><td>0.00065</td><td>25</td><td>25</td><td>13620289</td><td>99.42852</td></tr>\n",
       "\t<tr><td>0.00066</td><td>25</td><td>25</td><td>13619008</td><td>99.41917</td></tr>\n",
       "\t<tr><td>0.00067</td><td>25</td><td>25</td><td>13618358</td><td>99.41442</td></tr>\n",
       "\t<tr><td>0.00068</td><td>25</td><td>25</td><td>13617147</td><td>99.40558</td></tr>\n",
       "\t<tr><td>0.00069</td><td>25</td><td>25</td><td>13616100</td><td>99.39794</td></tr>\n",
       "\t<tr><td>0.00070</td><td>25</td><td>25</td><td>13615262</td><td>99.39182</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A df[,5]: 70 × 5\n",
       "\\begin{tabular}{r|lllll}\n",
       " threshold.value & control.taxa.count & control.taxa.matches & read.count & read.percent\\\\\n",
       " <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t 0.00001 & 32 & 25 & 13698507 & 99.99951\\\\\n",
       "\t 0.00002 & 32 & 25 & 13698047 & 99.99615\\\\\n",
       "\t 0.00003 & 29 & 25 & 13697298 & 99.99069\\\\\n",
       "\t 0.00004 & 29 & 25 & 13696500 & 99.98486\\\\\n",
       "\t 0.00005 & 29 & 25 & 13695537 & 99.97783\\\\\n",
       "\t 0.00006 & 29 & 25 & 13694424 & 99.96970\\\\\n",
       "\t 0.00007 & 29 & 25 & 13693231 & 99.96100\\\\\n",
       "\t 0.00008 & 28 & 25 & 13692359 & 99.95463\\\\\n",
       "\t 0.00009 & 28 & 25 & 13691054 & 99.94510\\\\\n",
       "\t 0.00010 & 28 & 25 & 13689760 & 99.93566\\\\\n",
       "\t 0.00011 & 28 & 25 & 13688361 & 99.92544\\\\\n",
       "\t 0.00012 & 28 & 25 & 13687044 & 99.91583\\\\\n",
       "\t 0.00013 & 28 & 25 & 13685916 & 99.90760\\\\\n",
       "\t 0.00014 & 28 & 25 & 13684498 & 99.89724\\\\\n",
       "\t 0.00015 & 28 & 25 & 13683125 & 99.88722\\\\\n",
       "\t 0.00016 & 28 & 25 & 13682026 & 99.87920\\\\\n",
       "\t 0.00017 & 27 & 25 & 13680575 & 99.86861\\\\\n",
       "\t 0.00018 & 27 & 25 & 13679073 & 99.85764\\\\\n",
       "\t 0.00019 & 27 & 25 & 13677622 & 99.84705\\\\\n",
       "\t 0.00020 & 27 & 25 & 13676524 & 99.83903\\\\\n",
       "\t 0.00021 & 27 & 25 & 13675156 & 99.82905\\\\\n",
       "\t 0.00022 & 27 & 25 & 13674016 & 99.82073\\\\\n",
       "\t 0.00023 & 27 & 25 & 13673039 & 99.81359\\\\\n",
       "\t 0.00024 & 27 & 25 & 13671602 & 99.80310\\\\\n",
       "\t 0.00025 & 27 & 25 & 13670326 & 99.79379\\\\\n",
       "\t 0.00026 & 27 & 25 & 13668995 & 99.78407\\\\\n",
       "\t 0.00027 & 27 & 25 & 13667588 & 99.77380\\\\\n",
       "\t 0.00028 & 27 & 25 & 13665666 & 99.75977\\\\\n",
       "\t 0.00029 & 27 & 25 & 13664530 & 99.75148\\\\\n",
       "\t 0.00030 & 27 & 25 & 13663359 & 99.74293\\\\\n",
       "\t ⋮ & ⋮ & ⋮ & ⋮ & ⋮\\\\\n",
       "\t 0.00041 & 26 & 25 & 13648667 & 99.63568\\\\\n",
       "\t 0.00042 & 26 & 25 & 13647442 & 99.62673\\\\\n",
       "\t 0.00043 & 26 & 25 & 13646378 & 99.61897\\\\\n",
       "\t 0.00044 & 26 & 25 & 13645423 & 99.61200\\\\\n",
       "\t 0.00045 & 26 & 25 & 13644717 & 99.60684\\\\\n",
       "\t 0.00046 & 26 & 25 & 13643418 & 99.59736\\\\\n",
       "\t 0.00047 & 26 & 25 & 13642649 & 99.59175\\\\\n",
       "\t 0.00048 & 26 & 25 & 13641861 & 99.58599\\\\\n",
       "\t 0.00049 & 26 & 25 & 13640887 & 99.57888\\\\\n",
       "\t 0.00050 & 26 & 25 & 13639816 & 99.57106\\\\\n",
       "\t 0.00051 & 26 & 25 & 13637863 & 99.55681\\\\\n",
       "\t 0.00052 & 26 & 25 & 13637181 & 99.55183\\\\\n",
       "\t 0.00053 & 26 & 25 & 13635759 & 99.54145\\\\\n",
       "\t 0.00054 & 26 & 25 & 13634625 & 99.53317\\\\\n",
       "\t 0.00055 & 26 & 25 & 13633344 & 99.52382\\\\\n",
       "\t 0.00056 & 26 & 25 & 13632121 & 99.51489\\\\\n",
       "\t 0.00057 & 26 & 25 & 13630886 & 99.50588\\\\\n",
       "\t 0.00058 & 26 & 25 & 13629658 & 99.49691\\\\\n",
       "\t 0.00059 & 26 & 25 & 13628585 & 99.48908\\\\\n",
       "\t 0.00060 & 26 & 25 & 13627639 & 99.48217\\\\\n",
       "\t 0.00061 & 26 & 25 & 13626268 & 99.47216\\\\\n",
       "\t 0.00062 & 26 & 25 & 13625068 & 99.46340\\\\\n",
       "\t 0.00063 & 26 & 25 & 13623688 & 99.45333\\\\\n",
       "\t 0.00064 & 26 & 25 & 13621808 & 99.43961\\\\\n",
       "\t 0.00065 & 25 & 25 & 13620289 & 99.42852\\\\\n",
       "\t 0.00066 & 25 & 25 & 13619008 & 99.41917\\\\\n",
       "\t 0.00067 & 25 & 25 & 13618358 & 99.41442\\\\\n",
       "\t 0.00068 & 25 & 25 & 13617147 & 99.40558\\\\\n",
       "\t 0.00069 & 25 & 25 & 13616100 & 99.39794\\\\\n",
       "\t 0.00070 & 25 & 25 & 13615262 & 99.39182\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A df[,5]: 70 × 5\n",
       "\n",
       "| threshold.value &lt;dbl&gt; | control.taxa.count &lt;dbl&gt; | control.taxa.matches &lt;dbl&gt; | read.count &lt;dbl&gt; | read.percent &lt;dbl&gt; |\n",
       "|---|---|---|---|---|\n",
       "| 0.00001 | 32 | 25 | 13698507 | 99.99951 |\n",
       "| 0.00002 | 32 | 25 | 13698047 | 99.99615 |\n",
       "| 0.00003 | 29 | 25 | 13697298 | 99.99069 |\n",
       "| 0.00004 | 29 | 25 | 13696500 | 99.98486 |\n",
       "| 0.00005 | 29 | 25 | 13695537 | 99.97783 |\n",
       "| 0.00006 | 29 | 25 | 13694424 | 99.96970 |\n",
       "| 0.00007 | 29 | 25 | 13693231 | 99.96100 |\n",
       "| 0.00008 | 28 | 25 | 13692359 | 99.95463 |\n",
       "| 0.00009 | 28 | 25 | 13691054 | 99.94510 |\n",
       "| 0.00010 | 28 | 25 | 13689760 | 99.93566 |\n",
       "| 0.00011 | 28 | 25 | 13688361 | 99.92544 |\n",
       "| 0.00012 | 28 | 25 | 13687044 | 99.91583 |\n",
       "| 0.00013 | 28 | 25 | 13685916 | 99.90760 |\n",
       "| 0.00014 | 28 | 25 | 13684498 | 99.89724 |\n",
       "| 0.00015 | 28 | 25 | 13683125 | 99.88722 |\n",
       "| 0.00016 | 28 | 25 | 13682026 | 99.87920 |\n",
       "| 0.00017 | 27 | 25 | 13680575 | 99.86861 |\n",
       "| 0.00018 | 27 | 25 | 13679073 | 99.85764 |\n",
       "| 0.00019 | 27 | 25 | 13677622 | 99.84705 |\n",
       "| 0.00020 | 27 | 25 | 13676524 | 99.83903 |\n",
       "| 0.00021 | 27 | 25 | 13675156 | 99.82905 |\n",
       "| 0.00022 | 27 | 25 | 13674016 | 99.82073 |\n",
       "| 0.00023 | 27 | 25 | 13673039 | 99.81359 |\n",
       "| 0.00024 | 27 | 25 | 13671602 | 99.80310 |\n",
       "| 0.00025 | 27 | 25 | 13670326 | 99.79379 |\n",
       "| 0.00026 | 27 | 25 | 13668995 | 99.78407 |\n",
       "| 0.00027 | 27 | 25 | 13667588 | 99.77380 |\n",
       "| 0.00028 | 27 | 25 | 13665666 | 99.75977 |\n",
       "| 0.00029 | 27 | 25 | 13664530 | 99.75148 |\n",
       "| 0.00030 | 27 | 25 | 13663359 | 99.74293 |\n",
       "| ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |\n",
       "| 0.00041 | 26 | 25 | 13648667 | 99.63568 |\n",
       "| 0.00042 | 26 | 25 | 13647442 | 99.62673 |\n",
       "| 0.00043 | 26 | 25 | 13646378 | 99.61897 |\n",
       "| 0.00044 | 26 | 25 | 13645423 | 99.61200 |\n",
       "| 0.00045 | 26 | 25 | 13644717 | 99.60684 |\n",
       "| 0.00046 | 26 | 25 | 13643418 | 99.59736 |\n",
       "| 0.00047 | 26 | 25 | 13642649 | 99.59175 |\n",
       "| 0.00048 | 26 | 25 | 13641861 | 99.58599 |\n",
       "| 0.00049 | 26 | 25 | 13640887 | 99.57888 |\n",
       "| 0.00050 | 26 | 25 | 13639816 | 99.57106 |\n",
       "| 0.00051 | 26 | 25 | 13637863 | 99.55681 |\n",
       "| 0.00052 | 26 | 25 | 13637181 | 99.55183 |\n",
       "| 0.00053 | 26 | 25 | 13635759 | 99.54145 |\n",
       "| 0.00054 | 26 | 25 | 13634625 | 99.53317 |\n",
       "| 0.00055 | 26 | 25 | 13633344 | 99.52382 |\n",
       "| 0.00056 | 26 | 25 | 13632121 | 99.51489 |\n",
       "| 0.00057 | 26 | 25 | 13630886 | 99.50588 |\n",
       "| 0.00058 | 26 | 25 | 13629658 | 99.49691 |\n",
       "| 0.00059 | 26 | 25 | 13628585 | 99.48908 |\n",
       "| 0.00060 | 26 | 25 | 13627639 | 99.48217 |\n",
       "| 0.00061 | 26 | 25 | 13626268 | 99.47216 |\n",
       "| 0.00062 | 26 | 25 | 13625068 | 99.46340 |\n",
       "| 0.00063 | 26 | 25 | 13623688 | 99.45333 |\n",
       "| 0.00064 | 26 | 25 | 13621808 | 99.43961 |\n",
       "| 0.00065 | 25 | 25 | 13620289 | 99.42852 |\n",
       "| 0.00066 | 25 | 25 | 13619008 | 99.41917 |\n",
       "| 0.00067 | 25 | 25 | 13618358 | 99.41442 |\n",
       "| 0.00068 | 25 | 25 | 13617147 | 99.40558 |\n",
       "| 0.00069 | 25 | 25 | 13616100 | 99.39794 |\n",
       "| 0.00070 | 25 | 25 | 13615262 | 99.39182 |\n",
       "\n"
      ],
      "text/plain": [
       "   threshold.value control.taxa.count control.taxa.matches read.count\n",
       "1  0.00001         32                 25                   13698507  \n",
       "2  0.00002         32                 25                   13698047  \n",
       "3  0.00003         29                 25                   13697298  \n",
       "4  0.00004         29                 25                   13696500  \n",
       "5  0.00005         29                 25                   13695537  \n",
       "6  0.00006         29                 25                   13694424  \n",
       "7  0.00007         29                 25                   13693231  \n",
       "8  0.00008         28                 25                   13692359  \n",
       "9  0.00009         28                 25                   13691054  \n",
       "10 0.00010         28                 25                   13689760  \n",
       "11 0.00011         28                 25                   13688361  \n",
       "12 0.00012         28                 25                   13687044  \n",
       "13 0.00013         28                 25                   13685916  \n",
       "14 0.00014         28                 25                   13684498  \n",
       "15 0.00015         28                 25                   13683125  \n",
       "16 0.00016         28                 25                   13682026  \n",
       "17 0.00017         27                 25                   13680575  \n",
       "18 0.00018         27                 25                   13679073  \n",
       "19 0.00019         27                 25                   13677622  \n",
       "20 0.00020         27                 25                   13676524  \n",
       "21 0.00021         27                 25                   13675156  \n",
       "22 0.00022         27                 25                   13674016  \n",
       "23 0.00023         27                 25                   13673039  \n",
       "24 0.00024         27                 25                   13671602  \n",
       "25 0.00025         27                 25                   13670326  \n",
       "26 0.00026         27                 25                   13668995  \n",
       "27 0.00027         27                 25                   13667588  \n",
       "28 0.00028         27                 25                   13665666  \n",
       "29 0.00029         27                 25                   13664530  \n",
       "30 0.00030         27                 25                   13663359  \n",
       "⋮  ⋮               ⋮                  ⋮                    ⋮         \n",
       "41 0.00041         26                 25                   13648667  \n",
       "42 0.00042         26                 25                   13647442  \n",
       "43 0.00043         26                 25                   13646378  \n",
       "44 0.00044         26                 25                   13645423  \n",
       "45 0.00045         26                 25                   13644717  \n",
       "46 0.00046         26                 25                   13643418  \n",
       "47 0.00047         26                 25                   13642649  \n",
       "48 0.00048         26                 25                   13641861  \n",
       "49 0.00049         26                 25                   13640887  \n",
       "50 0.00050         26                 25                   13639816  \n",
       "51 0.00051         26                 25                   13637863  \n",
       "52 0.00052         26                 25                   13637181  \n",
       "53 0.00053         26                 25                   13635759  \n",
       "54 0.00054         26                 25                   13634625  \n",
       "55 0.00055         26                 25                   13633344  \n",
       "56 0.00056         26                 25                   13632121  \n",
       "57 0.00057         26                 25                   13630886  \n",
       "58 0.00058         26                 25                   13629658  \n",
       "59 0.00059         26                 25                   13628585  \n",
       "60 0.00060         26                 25                   13627639  \n",
       "61 0.00061         26                 25                   13626268  \n",
       "62 0.00062         26                 25                   13625068  \n",
       "63 0.00063         26                 25                   13623688  \n",
       "64 0.00064         26                 25                   13621808  \n",
       "65 0.00065         25                 25                   13620289  \n",
       "66 0.00066         25                 25                   13619008  \n",
       "67 0.00067         25                 25                   13618358  \n",
       "68 0.00068         25                 25                   13617147  \n",
       "69 0.00069         25                 25                   13616100  \n",
       "70 0.00070         25                 25                   13615262  \n",
       "   read.percent\n",
       "1  99.99951    \n",
       "2  99.99615    \n",
       "3  99.99069    \n",
       "4  99.98486    \n",
       "5  99.97783    \n",
       "6  99.96970    \n",
       "7  99.96100    \n",
       "8  99.95463    \n",
       "9  99.94510    \n",
       "10 99.93566    \n",
       "11 99.92544    \n",
       "12 99.91583    \n",
       "13 99.90760    \n",
       "14 99.89724    \n",
       "15 99.88722    \n",
       "16 99.87920    \n",
       "17 99.86861    \n",
       "18 99.85764    \n",
       "19 99.84705    \n",
       "20 99.83903    \n",
       "21 99.82905    \n",
       "22 99.82073    \n",
       "23 99.81359    \n",
       "24 99.80310    \n",
       "25 99.79379    \n",
       "26 99.78407    \n",
       "27 99.77380    \n",
       "28 99.75977    \n",
       "29 99.75148    \n",
       "30 99.74293    \n",
       "⋮  ⋮           \n",
       "41 99.63568    \n",
       "42 99.62673    \n",
       "43 99.61897    \n",
       "44 99.61200    \n",
       "45 99.60684    \n",
       "46 99.59736    \n",
       "47 99.59175    \n",
       "48 99.58599    \n",
       "49 99.57888    \n",
       "50 99.57106    \n",
       "51 99.55681    \n",
       "52 99.55183    \n",
       "53 99.54145    \n",
       "54 99.53317    \n",
       "55 99.52382    \n",
       "56 99.51489    \n",
       "57 99.50588    \n",
       "58 99.49691    \n",
       "59 99.48908    \n",
       "60 99.48217    \n",
       "61 99.47216    \n",
       "62 99.46340    \n",
       "63 99.45333    \n",
       "64 99.43961    \n",
       "65 99.42852    \n",
       "66 99.41917    \n",
       "67 99.41442    \n",
       "68 99.40558    \n",
       "69 99.39794    \n",
       "70 99.39182    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(ws.threshold2 <- estimate.WSthreshold(ps = e3, WSrange = c(1e-5:7e-4, 1e-5), controlID = \"377\", controlFASTA = mock.fasta))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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KwsYbykwDOdBGV8i1auXElEI0eODAoK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1WhkLO0EQLM9gu+8jAChB2zcoqBVdPSnZ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\nkFMXdqy4btSokXAZhKnk5GT2/a1fv96RsTm/jh07SmbX06w5c+awr75Hjx7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DAAAAkAgUdgAAAAASgcIOAAAAQCJQ2AEAAABIBAo7KXjz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\nkAgUdgAAAAAS8f8Ahllg4h3T4ocAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot.threshold(ws.threshold2)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "As expected, our thresholds vary a bit between runs. For library two, the results suggest that a WS threshold of 6.5e-4 is sufficient to clean up the even positive control for that run. Despite this ~4-fold difference in threshold values between runs, this discrepancy is actually rather trivial, likely only affecting within-sample ASV thresholds by a few reads (eg. for a sample with 10,000 reads, the minimum number that an ASV would need to be retained would be increased by ~ 4 reads), so we're in pretty good shape. \n",
    "\n",
    "Because these values are so similar, we'll press forward as-is. However, for larger discrepancies, it's probably best to filter on a run-specific basis. Now that we've determined our WS threshold (6.5e-4), let's estimate our AS filter thresholds with this value as a fixed parameter. There are several global, AS filtering strategies for removing exogenous contaminants from marker gene datasets. Here, we focus on three popular approaches that can all be estimated and applied using the suite of functions sourced above. <br>\n",
    "<br>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"estimate.ASthreshold\"></a>\n",
    "# estimate.ASthreshold\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>ESTIMATE.ASTHRESHOLD</b><br>\n",
    "Performs AS filter threshold estimation by iterative application over a range of threshold values and filtering strategies. Supports the (optional) application of fixed thresholds if you want to optimize one or multiple threshold with the other(s) fixed. <br>\n",
    "<br>\n",
    "<b>Input:</b> <br>\n",
    "<b>ps:</b> a phyloseq-class dataset.<br>\n",
    "<br>\n",
    "<b>Parameters (all are optional):</b><br>\n",
    "<b>WST:</b> The WS threshold to apply before estimation of AS thresholds.<br>\n",
    "<b>mdCAT:</b> The sample data category used in conjunction with mdFACTOR for metadata based filtering.<br>\n",
    "<b>mdFACTOR:</b> The factor within mdCAT used for metadata based filtering.<br>\n",
    "<b>mdNEGATIVE:</b> A logical flag indicating whether metadata-based filtering should be positive (remove matching samples) or negative (remove non matching samples).<br>\n",
    "<b>minLIB:</b> The minimum sequence depth for a sample to be retained.<br>\n",
    "<b>RArange:</b> The range of relative abundance filter thresholds to iterate over, followed by the estimation interval. <br>\n",
    "<b>CVrange:</b> The range of CV filter thresholds to iterate over, followed by the estimation interval.<br>\n",
    "<b>PFrange:</b> The range of prevalence filter thresholds to iterate over, followed by the estimation interval. <br>\n",
    "<b>RAT:</b> Relative Abundance Threshold; the fixed percentage of reads across the dataset for which an ASV must be present for that ASV to be retained. <br>\n",
    "<b>CVT:</b> Coefficient of Variation Threshold; the fixed lowest CV value of an ASV for that ASV to be retained.<br>\n",
    "<b>PFT:</b> Prevalence Filter Threshold; the fixed percentage of samples across the dataset for which an ASV must be present for that ASV to be retained. <br>\n",
    "\n",
    "<br>\n",
    "<b>Output:</b> <br>\n",
    "<b>relative.abundance.filtering.stats:</b> The ASV count remaining in the dataset at the given relative abundance threshold. <br>\n",
    "<b>CV.filtering.stats:</b> The ASV count remaining in the dataset at the given CV threshold. <br>\n",
    "<b>prevalence.filtering.stats:</b> The ASV count remaining in the dataset at the given prevalence threshold. <br>\n",
    "<b>ASV.filtering.stats:</b> A dataframe listing the read count, read percent, prevalence count, prevalence percent, CV, taxonomic ranks, and sequence identity of each ASV.<br>\n",
    "\n",
    "</div> \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-success\">\n",
    "<b>TIP:</b> To manintain fidelity with the pipeline used by the <b>microfilter</b> function (and so that threshold estimation is accurate), <b>estimate.ASthreshold</b> supports WS threshold application and metadata and read count based sample filtering. That is, if you plan to remove any samples matching metadata identifiers or below a read count threshold using <b>microfilter</b>, it's best to apply those same metrics to the <b>estimate.ASthreshold</b> function for accurate threshold estimation. Samples removed prior to threshold estimation by <b>estimate.ASthreshold</b> are not permanently removed from the dataset. \n",
    "</div>\n",
    "<br>\n",
    "<br>\n",
    "We'll use the __estimate.ASthreshold__ function to simultaneously estimate all three filter thresholds.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Removing 27 samples with read count < 1000\n",
      "Applying WS filter threshold of 0.00065\n",
      "Removing 4 samples matching metadata identifiers Visit:Mock\n",
      "Estimating filtering statistics from relative abundance thresholds 1e-05 to 0.001 by 1e-05\n",
      "Estimating filtering statistics from CV thresholds 0 to 5 by 0.1\n",
      "Estimating filtering statistics from prevalence thresholds 0.01 to 0.1 by 0.005\n"
     ]
    }
   ],
   "source": [
    "as.threshold <- estimate.ASthreshold(ps = e3, WST = 6.5e-4, minLIB = 1000, mdFACTOR = \"Mock\", mdCAT = \"Visit\", Prange = c(0.01:0.1, 0.005), CVrange = c(0:5, 0.1), \n",
    "                                     RArange = c(1e-5:1e-3, 1e-5))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A df[,2]: 10 × 2</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>relative.abundance.filter</th><th scope=col>ASV.count</th></tr>\n",
       "\t<tr><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>1e-05</td><td>532</td></tr>\n",
       "\t<tr><td>2e-05</td><td>412</td></tr>\n",
       "\t<tr><td>3e-05</td><td>361</td></tr>\n",
       "\t<tr><td>4e-05</td><td>326</td></tr>\n",
       "\t<tr><td>5e-05</td><td>306</td></tr>\n",
       "\t<tr><td>6e-05</td><td>286</td></tr>\n",
       "\t<tr><td>7e-05</td><td>269</td></tr>\n",
       "\t<tr><td>8e-05</td><td>262</td></tr>\n",
       "\t<tr><td>9e-05</td><td>253</td></tr>\n",
       "\t<tr><td>1e-04</td><td>238</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A df[,2]: 10 × 2\n",
       "\\begin{tabular}{r|ll}\n",
       " relative.abundance.filter & ASV.count\\\\\n",
       " <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t 1e-05 & 532\\\\\n",
       "\t 2e-05 & 412\\\\\n",
       "\t 3e-05 & 361\\\\\n",
       "\t 4e-05 & 326\\\\\n",
       "\t 5e-05 & 306\\\\\n",
       "\t 6e-05 & 286\\\\\n",
       "\t 7e-05 & 269\\\\\n",
       "\t 8e-05 & 262\\\\\n",
       "\t 9e-05 & 253\\\\\n",
       "\t 1e-04 & 238\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A df[,2]: 10 × 2\n",
       "\n",
       "| relative.abundance.filter &lt;dbl&gt; | ASV.count &lt;dbl&gt; |\n",
       "|---|---|\n",
       "| 1e-05 | 532 |\n",
       "| 2e-05 | 412 |\n",
       "| 3e-05 | 361 |\n",
       "| 4e-05 | 326 |\n",
       "| 5e-05 | 306 |\n",
       "| 6e-05 | 286 |\n",
       "| 7e-05 | 269 |\n",
       "| 8e-05 | 262 |\n",
       "| 9e-05 | 253 |\n",
       "| 1e-04 | 238 |\n",
       "\n"
      ],
      "text/plain": [
       "   relative.abundance.filter ASV.count\n",
       "1  1e-05                     532      \n",
       "2  2e-05                     412      \n",
       "3  3e-05                     361      \n",
       "4  4e-05                     326      \n",
       "5  5e-05                     306      \n",
       "6  6e-05                     286      \n",
       "7  7e-05                     269      \n",
       "8  8e-05                     262      \n",
       "9  9e-05                     253      \n",
       "10 1e-04                     238      "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "as.threshold$relative.abundance.filtering.stats[1:10,]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A df[,2]: 10 × 2</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>CV.filter</th><th scope=col>ASV.count</th></tr>\n",
       "\t<tr><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.0</td><td>1642</td></tr>\n",
       "\t<tr><td>0.1</td><td>1642</td></tr>\n",
       "\t<tr><td>0.2</td><td>1642</td></tr>\n",
       "\t<tr><td>0.3</td><td>1642</td></tr>\n",
       "\t<tr><td>0.4</td><td>1642</td></tr>\n",
       "\t<tr><td>0.5</td><td>1642</td></tr>\n",
       "\t<tr><td>0.6</td><td>1642</td></tr>\n",
       "\t<tr><td>0.7</td><td>1642</td></tr>\n",
       "\t<tr><td>0.8</td><td>1642</td></tr>\n",
       "\t<tr><td>0.9</td><td>1642</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A df[,2]: 10 × 2\n",
       "\\begin{tabular}{r|ll}\n",
       " CV.filter & ASV.count\\\\\n",
       " <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t 0.0 & 1642\\\\\n",
       "\t 0.1 & 1642\\\\\n",
       "\t 0.2 & 1642\\\\\n",
       "\t 0.3 & 1642\\\\\n",
       "\t 0.4 & 1642\\\\\n",
       "\t 0.5 & 1642\\\\\n",
       "\t 0.6 & 1642\\\\\n",
       "\t 0.7 & 1642\\\\\n",
       "\t 0.8 & 1642\\\\\n",
       "\t 0.9 & 1642\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A df[,2]: 10 × 2\n",
       "\n",
       "| CV.filter &lt;dbl&gt; | ASV.count &lt;dbl&gt; |\n",
       "|---|---|\n",
       "| 0.0 | 1642 |\n",
       "| 0.1 | 1642 |\n",
       "| 0.2 | 1642 |\n",
       "| 0.3 | 1642 |\n",
       "| 0.4 | 1642 |\n",
       "| 0.5 | 1642 |\n",
       "| 0.6 | 1642 |\n",
       "| 0.7 | 1642 |\n",
       "| 0.8 | 1642 |\n",
       "| 0.9 | 1642 |\n",
       "\n"
      ],
      "text/plain": [
       "   CV.filter ASV.count\n",
       "1  0.0       1642     \n",
       "2  0.1       1642     \n",
       "3  0.2       1642     \n",
       "4  0.3       1642     \n",
       "5  0.4       1642     \n",
       "6  0.5       1642     \n",
       "7  0.6       1642     \n",
       "8  0.7       1642     \n",
       "9  0.8       1642     \n",
       "10 0.9       1642     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "as.threshold$CV.filtering.stats[1:10,]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A df[,2]: 10 × 2</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>prevalence.filter</th><th scope=col>ASV.count</th></tr>\n",
       "\t<tr><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.010</td><td>298</td></tr>\n",
       "\t<tr><td>0.015</td><td>220</td></tr>\n",
       "\t<tr><td>0.020</td><td>196</td></tr>\n",
       "\t<tr><td>0.025</td><td>168</td></tr>\n",
       "\t<tr><td>0.030</td><td>146</td></tr>\n",
       "\t<tr><td>0.035</td><td>125</td></tr>\n",
       "\t<tr><td>0.040</td><td>118</td></tr>\n",
       "\t<tr><td>0.045</td><td>111</td></tr>\n",
       "\t<tr><td>0.050</td><td>109</td></tr>\n",
       "\t<tr><td>0.055</td><td>104</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A df[,2]: 10 × 2\n",
       "\\begin{tabular}{r|ll}\n",
       " prevalence.filter & ASV.count\\\\\n",
       " <dbl> & <int>\\\\\n",
       "\\hline\n",
       "\t 0.010 & 298\\\\\n",
       "\t 0.015 & 220\\\\\n",
       "\t 0.020 & 196\\\\\n",
       "\t 0.025 & 168\\\\\n",
       "\t 0.030 & 146\\\\\n",
       "\t 0.035 & 125\\\\\n",
       "\t 0.040 & 118\\\\\n",
       "\t 0.045 & 111\\\\\n",
       "\t 0.050 & 109\\\\\n",
       "\t 0.055 & 104\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A df[,2]: 10 × 2\n",
       "\n",
       "| prevalence.filter &lt;dbl&gt; | ASV.count &lt;int&gt; |\n",
       "|---|---|\n",
       "| 0.010 | 298 |\n",
       "| 0.015 | 220 |\n",
       "| 0.020 | 196 |\n",
       "| 0.025 | 168 |\n",
       "| 0.030 | 146 |\n",
       "| 0.035 | 125 |\n",
       "| 0.040 | 118 |\n",
       "| 0.045 | 111 |\n",
       "| 0.050 | 109 |\n",
       "| 0.055 | 104 |\n",
       "\n"
      ],
      "text/plain": [
       "   prevalence.filter ASV.count\n",
       "1  0.010             298      \n",
       "2  0.015             220      \n",
       "3  0.020             196      \n",
       "4  0.025             168      \n",
       "5  0.030             146      \n",
       "6  0.035             125      \n",
       "7  0.040             118      \n",
       "8  0.045             111      \n",
       "9  0.050             109      \n",
       "10 0.055             104      "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "as.threshold$prevalence.filtering.stats[1:10,]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A df[,13]: 10 × 13</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>ASV.read.count</th><th scope=col>ASV.read.percent</th><th scope=col>ASV.prevalence</th><th scope=col>ASV.prevalence.percent</th><th scope=col>ASV.CV</th><th scope=col>Kingdom</th><th scope=col>Phylum</th><th scope=col>Class</th><th scope=col>Order</th><th scope=col>Family</th><th scope=col>Genus</th><th scope=col>Species</th><th scope=col>ASV.ID</th></tr>\n",
       "\t<tr><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>2821241</td><td>20.734208</td><td>307</td><td>87.464387</td><td> 1.137142</td><td>Bacteria</td><td>Firmicutes    </td><td>Bacilli            </td><td>Lactobacillales  </td><td>Lactobacillaceae  </td><td>Lactobacillus       </td><td>iners                                 </td><td>TAGGGAATCTTCCACAATGGACGCAAGTCTGATGGAGCAACGCCGCGTGAGTGAAGAAGGGTTTCGGCTCGTAAAGCTCTGTTGTTGGTGAAGAAGGACAGGGGTAGTAACTGACCTTTGTTTGACGGTAATCAATTAGAAAGTCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGTGCAGGCGGCTCGATAAGTCTGATGTGAAAGCCTTCGGCTCAACCGGAGAATTGCATCAGAAACTGTCGAGCTTGAGTACAGAAGAGGAGAGTGGAACTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAAGAACACCGGTGGCGAAGGCGGCTCTCTGGTCTGTTACTGACGCTGAGGCTCGAAAGCATGGGTAGCGAACAGG</td></tr>\n",
       "\t<tr><td>1163923</td><td> 8.554044</td><td>140</td><td>39.886040</td><td> 2.368573</td><td>Bacteria</td><td>Firmicutes    </td><td>Clostridia         </td><td>Clostridiales    </td><td>Lachnospiraceae   </td><td>NA                  </td><td>NA                                    </td><td>TGGGGAATATTGCACAATGGGCGAAAGCCTGATGCAGCGACGCCGCGTGAGCGAAGAAGTATTTCGGTATGTAAAGCTCTATCAGAAGGGAAGAAAATGACGGTACCTTACTAAGAAGCTCCGGCTAAATACGTGCCAGCAGCCGCGGTAATACGTATGGAGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGTGTAGGCGGCACTATAAGTCTGATGTGAAAACCTAAGGCTTAACCATAGGATTGCATTGGAAACTGTAGAGCTGGAGTATCGGAGAGGCAAGCGGAATTCCTGGTGTAGTGGTGAAATACGTAGATATCAGGAAGAACATCGGTGGCGAAGGCGGCTTGCTGGACGATAACTGACGCTAAGGCTCGAAAGCGTGGGAAGCGAACAGG                         </td></tr>\n",
       "\t<tr><td> 803447</td><td> 5.904790</td><td> 94</td><td>26.780627</td><td> 3.209890</td><td>Bacteria</td><td>Firmicutes    </td><td>Bacilli            </td><td>Lactobacillales  </td><td>Lactobacillaceae  </td><td>Lactobacillus       </td><td>acidophilus/casei/crispatus/gallinarum</td><td>TAGGGAATCTTCCACAATGGACGCAAGTCTGATGGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTTGGTGAAGAAGGATAGAGGTAGTAACTGGCCTTTATTTGACGGTAATCAACCAGAAAGTCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGCGCAGGCGGAAGAATAAGTCTGATGTGAAAGCCCTCGGCTTAACCGAGGAACTGCATCGGAAACTGTTTTTCTTGAGTGCAGAAGAGGAGAGTGGAACTCCATGTGTAGCGGTGGAATGCGTAGATATATGGAAGAACACCAGTGGCGAAGGCGGCTCTCTGGTCTGCAACTGACGCTGAGGCTCGAAAGCATGGGTAGCGAACAGG</td></tr>\n",
       "\t<tr><td> 603155</td><td> 4.432780</td><td>107</td><td>30.484330</td><td> 2.535069</td><td>Bacteria</td><td>Firmicutes    </td><td>Bacilli            </td><td>Lactobacillales  </td><td>Lactobacillaceae  </td><td>Lactobacillus       </td><td>NA                                    </td><td>TAGGGAATCTTCCACAATGGACGCAAGTCTGATGGAGCAACGCCGCGTGAGTGAAGAAGGGTTTCGGCTCGTAAAGCTCTGTTGTTGGTGAAGAAGGACAGGGGTAGTAACTGACCTTTGTTTGACGGTAATCAATTAGAAAGTCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGTGCAGGCGGTTCGATAAGTCTGATGTGAAAGCCTTCGGCTCAACCGGAGAATTGCATCAGAAACTGTCGAGCTTGAGTACAGAAGAGGAGAGTGGAACTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAAGAACACCGGTGGCGAAGGCGGCTCTCTGGTCTGTTACTGACGCTGAGGCTCGAAAGCATGGGTAGCGAACAGG</td></tr>\n",
       "\t<tr><td> 502779</td><td> 3.695085</td><td>126</td><td>35.897436</td><td> 2.550646</td><td>Bacteria</td><td>Actinobacteria</td><td>Actinobacteria     </td><td>Bifidobacteriales</td><td>Bifidobacteriaceae</td><td>Gardnerella         </td><td>vaginalis                             </td><td>TGGGGAATATTGCGCAATGGGGGAAACCCTGACGCAGCGACGCCGCGTGCGGGATGAAGGCCTTCGGGTTGTAAACCGCTTTTGATTGGGAGCAAGCTTTCGGGTGAGTGTACCTTTCGAATAAGCGCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGCGCAAGCGTTATCCGGAATTATTGGGCGTAAAGAGCTTGTAGGCGGTTCGTCGCGTCTGGTGTGAAAGCCCATCGCTTAACGGTGGGTCTGCGCCGGGTACGGGCGGGCTAGAGTGCAGTAGGGGAGACTGGAATTCCCGGTGTAACGGTGGAATGTGTAGATATCGGGAAGAACACCAATGGCGAAGGCAGGTCTCTGGGCTGTTACTGACGCTGAGAAGCGAAAGCGTGGGGAGCGAACAGG                  </td></tr>\n",
       "\t<tr><td> 444239</td><td> 3.264855</td><td>158</td><td>45.014245</td><td> 1.806534</td><td>Bacteria</td><td>Firmicutes    </td><td>Negativicutes      </td><td>Selenomonadales  </td><td>Veillonellaceae   </td><td>Megasphaera         </td><td>NA                                    </td><td>TGGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGCCGCGTGAGTGAAGAAGGTCTTCGGATTGTAAAGCTCTGTTATACGGGACGAAAAAGACGGATGCCAACAGTATCCGTCCGTGACGGTACCGTAAGAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGAATTATTGGGCGTAAAGGGCGCGCAGGCGGTTCGGTAAGTCTGTCTTAAAAGTGCGGGGCTTAACCCCGTGAGGGGACGGAAACTGTCGAACTTGAGTGTCGGAGAGGAAAGCGGAATTCCTAGTGTAGCGGTGAAATGCGTAGATATTAGGAGGAACACCGGTGGCGAAAGCGGCTTTCTGGACGACAACTGACGCTGAGGCGCGAAAGCGTGGGGAGCAAACAGG</td></tr>\n",
       "\t<tr><td> 261842</td><td> 1.924361</td><td>  4</td><td> 1.139601</td><td>11.256905</td><td>Bacteria</td><td>Firmicutes    </td><td>Bacilli            </td><td>Lactobacillales  </td><td>Streptococcaceae  </td><td>Streptococcus       </td><td>mutans                                </td><td>TAGGGAATCTTCGGCAATGGACGAAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTAAGTCAAGAACGTGTGTGAGAGTGGAAAGTTCACACAGTGACGGTAGCTTACCAGAAAGGGACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTCCCGAGCGTTGTCCGGATTTATTGGGCGTAAAGGGAGCGCAGGCGGTCAGGAAAGTCTGGAGTAAAAGGCTATGGCTCAACCATAGTGTGCTCTGGAAACTGTCTGACTTGAGTGCAGAAGGGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCAGTGGCGAAAGCGGCTCTCTGGTCTGTCACTGACGCTGAGGCTCGAAAGCGTGGGTAGCGAACAGG</td></tr>\n",
       "\t<tr><td> 247625</td><td> 1.819876</td><td> 16</td><td> 4.558405</td><td> 9.754440</td><td>Bacteria</td><td>Proteobacteria</td><td>Gammaproteobacteria</td><td>Enterobacteriales</td><td>Enterobacteriaceae</td><td>Escherichia/Shigella</td><td>NA                                    </td><td>TGGGGAATATTGCACAATGGGCGCAAGCCTGATGCAGCCATGCCGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAAGGGAGTAAAGTTAATACCTTTGCTCATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGCACGCAGGCGGTTTGTTAAGTCAGATGTGAAATCCCCGGGCTCAACCTGGGAACTGCATCTGATACTGGCAAGCTTGAGTCTCGTAGAGGGGGGTAGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCGAAGGCGGCCCCCTGGACGAAGACTGACGCTCAGGTGCGAAAGCGTGGGGAGCAAACAGG</td></tr>\n",
       "\t<tr><td> 247551</td><td> 1.819332</td><td>123</td><td>35.042735</td><td> 2.480154</td><td>Bacteria</td><td>Fusobacteria  </td><td>Fusobacteriia      </td><td>Fusobacteriales  </td><td>Leptotrichiaceae  </td><td>Sneathia            </td><td>sanguinegens                          </td><td>TGGGGAATATTGGACAATGGAGGGAACTCTGATCCAGCAATTCTGTGTGTGTGAAGAAGGTTTTAGGACTGTAAAACACTTTTAGTAGGGAAGAAAAAAATGACGGTACCTACAGAAGAAGCAACGGCTAAATACGTGCCAGCAGCCGCGGTAATACGTATGTTGCGAGCGTTATCCGGAATTATTGGGCTTAAAGGGCATCTAGGCGGTAAGACAAGTTGAAGGTGAAAACCTGTGGCTCAACCATAGGCTTGCCTACAAAACTGTTGAACTAGAGTACTGGAAAGGTGGGTGGAACTACACGAGTAGAGGTGAAATTCGTAGATATGTGTAGGAATGCCGATGATGAAGATAACTCACTGGACAGAAACTGACGCTGAAGTGCGAAAGCTAGGGGAGCAAACAGG                      </td></tr>\n",
       "\t<tr><td> 240660</td><td> 1.768688</td><td>134</td><td>38.176638</td><td> 2.570635</td><td>Bacteria</td><td>Fusobacteria  </td><td>Fusobacteriia      </td><td>Fusobacteriales  </td><td>Leptotrichiaceae  </td><td>Sneathia            </td><td>sanguinegens                          </td><td>TGGGGAATATTGGACAATGGAGGCAACTCTGATCCAGCAATTCTGTGTGTGTGAAGAAGGTTTTAGGACTGTAAAACACTTTTAGTAGGGAAGAAAGAAATGACGGTACCTACAGAAGAAGCGACGGCTAAATACGTGCCAGCAGCCGCGGTAATACGTATGTCGCGAGCGTTATCCGGAATTATTGGGCTTAAAGGGCATCTAGGCGGTTAAACAAGTTGAAGGTGAAAACCTGTGGCTCAACCATAGGCTTGCCTACAAAACTGTATAACTAGAGTACTGGAAAGGTGGGTGGAACTACACGAGTAGAGGTGAAATTCGTAGATATGTGTAGGAATGCCGATGATGAAGATAACTCACTGGACAGCAACTGACGCTGAAGTGCGAAAGCTAGGGGAGCAAACAGG                      </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A df[,13]: 10 × 13\n",
       "\\begin{tabular}{r|lllllllllllll}\n",
       " ASV.read.count & ASV.read.percent & ASV.prevalence & ASV.prevalence.percent & ASV.CV & Kingdom & Phylum & Class & Order & Family & Genus & Species & ASV.ID\\\\\n",
       " <dbl> & <dbl> & <int> & <dbl> & <dbl> & <fct> & <fct> & <fct> & <fct> & <fct> & <fct> & <fct> & <fct>\\\\\n",
       "\\hline\n",
       "\t 2821241 & 20.734208 & 307 & 87.464387 &  1.137142 & Bacteria & Firmicutes     & Bacilli             & Lactobacillales   & Lactobacillaceae   & Lactobacillus        & iners                                  & TAGGGAATCTTCCACAATGGACGCAAGTCTGATGGAGCAACGCCGCGTGAGTGAAGAAGGGTTTCGGCTCGTAAAGCTCTGTTGTTGGTGAAGAAGGACAGGGGTAGTAACTGACCTTTGTTTGACGGTAATCAATTAGAAAGTCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGTGCAGGCGGCTCGATAAGTCTGATGTGAAAGCCTTCGGCTCAACCGGAGAATTGCATCAGAAACTGTCGAGCTTGAGTACAGAAGAGGAGAGTGGAACTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAAGAACACCGGTGGCGAAGGCGGCTCTCTGGTCTGTTACTGACGCTGAGGCTCGAAAGCATGGGTAGCGAACAGG\\\\\n",
       "\t 1163923 &  8.554044 & 140 & 39.886040 &  2.368573 & Bacteria & Firmicutes     & Clostridia          & Clostridiales     & Lachnospiraceae    & NA                   & NA                                     & TGGGGAATATTGCACAATGGGCGAAAGCCTGATGCAGCGACGCCGCGTGAGCGAAGAAGTATTTCGGTATGTAAAGCTCTATCAGAAGGGAAGAAAATGACGGTACCTTACTAAGAAGCTCCGGCTAAATACGTGCCAGCAGCCGCGGTAATACGTATGGAGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGTGTAGGCGGCACTATAAGTCTGATGTGAAAACCTAAGGCTTAACCATAGGATTGCATTGGAAACTGTAGAGCTGGAGTATCGGAGAGGCAAGCGGAATTCCTGGTGTAGTGGTGAAATACGTAGATATCAGGAAGAACATCGGTGGCGAAGGCGGCTTGCTGGACGATAACTGACGCTAAGGCTCGAAAGCGTGGGAAGCGAACAGG                         \\\\\n",
       "\t  803447 &  5.904790 &  94 & 26.780627 &  3.209890 & Bacteria & Firmicutes     & Bacilli             & Lactobacillales   & Lactobacillaceae   & Lactobacillus        & acidophilus/casei/crispatus/gallinarum & TAGGGAATCTTCCACAATGGACGCAAGTCTGATGGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTTGGTGAAGAAGGATAGAGGTAGTAACTGGCCTTTATTTGACGGTAATCAACCAGAAAGTCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGCGCAGGCGGAAGAATAAGTCTGATGTGAAAGCCCTCGGCTTAACCGAGGAACTGCATCGGAAACTGTTTTTCTTGAGTGCAGAAGAGGAGAGTGGAACTCCATGTGTAGCGGTGGAATGCGTAGATATATGGAAGAACACCAGTGGCGAAGGCGGCTCTCTGGTCTGCAACTGACGCTGAGGCTCGAAAGCATGGGTAGCGAACAGG\\\\\n",
       "\t  603155 &  4.432780 & 107 & 30.484330 &  2.535069 & Bacteria & Firmicutes     & Bacilli             & Lactobacillales   & Lactobacillaceae   & Lactobacillus        & NA                                     & TAGGGAATCTTCCACAATGGACGCAAGTCTGATGGAGCAACGCCGCGTGAGTGAAGAAGGGTTTCGGCTCGTAAAGCTCTGTTGTTGGTGAAGAAGGACAGGGGTAGTAACTGACCTTTGTTTGACGGTAATCAATTAGAAAGTCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGTGCAGGCGGTTCGATAAGTCTGATGTGAAAGCCTTCGGCTCAACCGGAGAATTGCATCAGAAACTGTCGAGCTTGAGTACAGAAGAGGAGAGTGGAACTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAAGAACACCGGTGGCGAAGGCGGCTCTCTGGTCTGTTACTGACGCTGAGGCTCGAAAGCATGGGTAGCGAACAGG\\\\\n",
       "\t  502779 &  3.695085 & 126 & 35.897436 &  2.550646 & Bacteria & Actinobacteria & Actinobacteria      & Bifidobacteriales & Bifidobacteriaceae & Gardnerella          & vaginalis                              & TGGGGAATATTGCGCAATGGGGGAAACCCTGACGCAGCGACGCCGCGTGCGGGATGAAGGCCTTCGGGTTGTAAACCGCTTTTGATTGGGAGCAAGCTTTCGGGTGAGTGTACCTTTCGAATAAGCGCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGCGCAAGCGTTATCCGGAATTATTGGGCGTAAAGAGCTTGTAGGCGGTTCGTCGCGTCTGGTGTGAAAGCCCATCGCTTAACGGTGGGTCTGCGCCGGGTACGGGCGGGCTAGAGTGCAGTAGGGGAGACTGGAATTCCCGGTGTAACGGTGGAATGTGTAGATATCGGGAAGAACACCAATGGCGAAGGCAGGTCTCTGGGCTGTTACTGACGCTGAGAAGCGAAAGCGTGGGGAGCGAACAGG                  \\\\\n",
       "\t  444239 &  3.264855 & 158 & 45.014245 &  1.806534 & Bacteria & Firmicutes     & Negativicutes       & Selenomonadales   & Veillonellaceae    & Megasphaera          & NA                                     & TGGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGCCGCGTGAGTGAAGAAGGTCTTCGGATTGTAAAGCTCTGTTATACGGGACGAAAAAGACGGATGCCAACAGTATCCGTCCGTGACGGTACCGTAAGAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGAATTATTGGGCGTAAAGGGCGCGCAGGCGGTTCGGTAAGTCTGTCTTAAAAGTGCGGGGCTTAACCCCGTGAGGGGACGGAAACTGTCGAACTTGAGTGTCGGAGAGGAAAGCGGAATTCCTAGTGTAGCGGTGAAATGCGTAGATATTAGGAGGAACACCGGTGGCGAAAGCGGCTTTCTGGACGACAACTGACGCTGAGGCGCGAAAGCGTGGGGAGCAAACAGG\\\\\n",
       "\t  261842 &  1.924361 &   4 &  1.139601 & 11.256905 & Bacteria & Firmicutes     & Bacilli             & Lactobacillales   & Streptococcaceae   & Streptococcus        & mutans                                 & TAGGGAATCTTCGGCAATGGACGAAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTAAGTCAAGAACGTGTGTGAGAGTGGAAAGTTCACACAGTGACGGTAGCTTACCAGAAAGGGACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTCCCGAGCGTTGTCCGGATTTATTGGGCGTAAAGGGAGCGCAGGCGGTCAGGAAAGTCTGGAGTAAAAGGCTATGGCTCAACCATAGTGTGCTCTGGAAACTGTCTGACTTGAGTGCAGAAGGGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCAGTGGCGAAAGCGGCTCTCTGGTCTGTCACTGACGCTGAGGCTCGAAAGCGTGGGTAGCGAACAGG\\\\\n",
       "\t  247625 &  1.819876 &  16 &  4.558405 &  9.754440 & Bacteria & Proteobacteria & Gammaproteobacteria & Enterobacteriales & Enterobacteriaceae & Escherichia/Shigella & NA                                     & TGGGGAATATTGCACAATGGGCGCAAGCCTGATGCAGCCATGCCGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAAGGGAGTAAAGTTAATACCTTTGCTCATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGCACGCAGGCGGTTTGTTAAGTCAGATGTGAAATCCCCGGGCTCAACCTGGGAACTGCATCTGATACTGGCAAGCTTGAGTCTCGTAGAGGGGGGTAGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCGAAGGCGGCCCCCTGGACGAAGACTGACGCTCAGGTGCGAAAGCGTGGGGAGCAAACAGG\\\\\n",
       "\t  247551 &  1.819332 & 123 & 35.042735 &  2.480154 & Bacteria & Fusobacteria   & Fusobacteriia       & Fusobacteriales   & Leptotrichiaceae   & Sneathia             & sanguinegens                           & TGGGGAATATTGGACAATGGAGGGAACTCTGATCCAGCAATTCTGTGTGTGTGAAGAAGGTTTTAGGACTGTAAAACACTTTTAGTAGGGAAGAAAAAAATGACGGTACCTACAGAAGAAGCAACGGCTAAATACGTGCCAGCAGCCGCGGTAATACGTATGTTGCGAGCGTTATCCGGAATTATTGGGCTTAAAGGGCATCTAGGCGGTAAGACAAGTTGAAGGTGAAAACCTGTGGCTCAACCATAGGCTTGCCTACAAAACTGTTGAACTAGAGTACTGGAAAGGTGGGTGGAACTACACGAGTAGAGGTGAAATTCGTAGATATGTGTAGGAATGCCGATGATGAAGATAACTCACTGGACAGAAACTGACGCTGAAGTGCGAAAGCTAGGGGAGCAAACAGG                      \\\\\n",
       "\t  240660 &  1.768688 & 134 & 38.176638 &  2.570635 & Bacteria & Fusobacteria   & Fusobacteriia       & Fusobacteriales   & Leptotrichiaceae   & Sneathia             & sanguinegens                           & TGGGGAATATTGGACAATGGAGGCAACTCTGATCCAGCAATTCTGTGTGTGTGAAGAAGGTTTTAGGACTGTAAAACACTTTTAGTAGGGAAGAAAGAAATGACGGTACCTACAGAAGAAGCGACGGCTAAATACGTGCCAGCAGCCGCGGTAATACGTATGTCGCGAGCGTTATCCGGAATTATTGGGCTTAAAGGGCATCTAGGCGGTTAAACAAGTTGAAGGTGAAAACCTGTGGCTCAACCATAGGCTTGCCTACAAAACTGTATAACTAGAGTACTGGAAAGGTGGGTGGAACTACACGAGTAGAGGTGAAATTCGTAGATATGTGTAGGAATGCCGATGATGAAGATAACTCACTGGACAGCAACTGACGCTGAAGTGCGAAAGCTAGGGGAGCAAACAGG                      \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A df[,13]: 10 × 13\n",
       "\n",
       "| ASV.read.count &lt;dbl&gt; | ASV.read.percent &lt;dbl&gt; | ASV.prevalence &lt;int&gt; | ASV.prevalence.percent &lt;dbl&gt; | ASV.CV &lt;dbl&gt; | Kingdom &lt;fct&gt; | Phylum &lt;fct&gt; | Class &lt;fct&gt; | Order &lt;fct&gt; | Family &lt;fct&gt; | Genus &lt;fct&gt; | Species &lt;fct&gt; | ASV.ID &lt;fct&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| 2821241 | 20.734208 | 307 | 87.464387 |  1.137142 | Bacteria | Firmicutes     | Bacilli             | Lactobacillales   | Lactobacillaceae   | Lactobacillus        | iners                                  | TAGGGAATCTTCCACAATGGACGCAAGTCTGATGGAGCAACGCCGCGTGAGTGAAGAAGGGTTTCGGCTCGTAAAGCTCTGTTGTTGGTGAAGAAGGACAGGGGTAGTAACTGACCTTTGTTTGACGGTAATCAATTAGAAAGTCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGTGCAGGCGGCTCGATAAGTCTGATGTGAAAGCCTTCGGCTCAACCGGAGAATTGCATCAGAAACTGTCGAGCTTGAGTACAGAAGAGGAGAGTGGAACTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAAGAACACCGGTGGCGAAGGCGGCTCTCTGGTCTGTTACTGACGCTGAGGCTCGAAAGCATGGGTAGCGAACAGG |\n",
       "| 1163923 |  8.554044 | 140 | 39.886040 |  2.368573 | Bacteria | Firmicutes     | Clostridia          | Clostridiales     | Lachnospiraceae    | NA                   | NA                                     | TGGGGAATATTGCACAATGGGCGAAAGCCTGATGCAGCGACGCCGCGTGAGCGAAGAAGTATTTCGGTATGTAAAGCTCTATCAGAAGGGAAGAAAATGACGGTACCTTACTAAGAAGCTCCGGCTAAATACGTGCCAGCAGCCGCGGTAATACGTATGGAGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGTGTAGGCGGCACTATAAGTCTGATGTGAAAACCTAAGGCTTAACCATAGGATTGCATTGGAAACTGTAGAGCTGGAGTATCGGAGAGGCAAGCGGAATTCCTGGTGTAGTGGTGAAATACGTAGATATCAGGAAGAACATCGGTGGCGAAGGCGGCTTGCTGGACGATAACTGACGCTAAGGCTCGAAAGCGTGGGAAGCGAACAGG                          |\n",
       "|  803447 |  5.904790 |  94 | 26.780627 |  3.209890 | Bacteria | Firmicutes     | Bacilli             | Lactobacillales   | Lactobacillaceae   | Lactobacillus        | acidophilus/casei/crispatus/gallinarum | TAGGGAATCTTCCACAATGGACGCAAGTCTGATGGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTTGGTGAAGAAGGATAGAGGTAGTAACTGGCCTTTATTTGACGGTAATCAACCAGAAAGTCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGCGCAGGCGGAAGAATAAGTCTGATGTGAAAGCCCTCGGCTTAACCGAGGAACTGCATCGGAAACTGTTTTTCTTGAGTGCAGAAGAGGAGAGTGGAACTCCATGTGTAGCGGTGGAATGCGTAGATATATGGAAGAACACCAGTGGCGAAGGCGGCTCTCTGGTCTGCAACTGACGCTGAGGCTCGAAAGCATGGGTAGCGAACAGG |\n",
       "|  603155 |  4.432780 | 107 | 30.484330 |  2.535069 | Bacteria | Firmicutes     | Bacilli             | Lactobacillales   | Lactobacillaceae   | Lactobacillus        | NA                                     | TAGGGAATCTTCCACAATGGACGCAAGTCTGATGGAGCAACGCCGCGTGAGTGAAGAAGGGTTTCGGCTCGTAAAGCTCTGTTGTTGGTGAAGAAGGACAGGGGTAGTAACTGACCTTTGTTTGACGGTAATCAATTAGAAAGTCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGTGCAGGCGGTTCGATAAGTCTGATGTGAAAGCCTTCGGCTCAACCGGAGAATTGCATCAGAAACTGTCGAGCTTGAGTACAGAAGAGGAGAGTGGAACTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAAGAACACCGGTGGCGAAGGCGGCTCTCTGGTCTGTTACTGACGCTGAGGCTCGAAAGCATGGGTAGCGAACAGG |\n",
       "|  502779 |  3.695085 | 126 | 35.897436 |  2.550646 | Bacteria | Actinobacteria | Actinobacteria      | Bifidobacteriales | Bifidobacteriaceae | Gardnerella          | vaginalis                              | TGGGGAATATTGCGCAATGGGGGAAACCCTGACGCAGCGACGCCGCGTGCGGGATGAAGGCCTTCGGGTTGTAAACCGCTTTTGATTGGGAGCAAGCTTTCGGGTGAGTGTACCTTTCGAATAAGCGCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGCGCAAGCGTTATCCGGAATTATTGGGCGTAAAGAGCTTGTAGGCGGTTCGTCGCGTCTGGTGTGAAAGCCCATCGCTTAACGGTGGGTCTGCGCCGGGTACGGGCGGGCTAGAGTGCAGTAGGGGAGACTGGAATTCCCGGTGTAACGGTGGAATGTGTAGATATCGGGAAGAACACCAATGGCGAAGGCAGGTCTCTGGGCTGTTACTGACGCTGAGAAGCGAAAGCGTGGGGAGCGAACAGG                   |\n",
       "|  444239 |  3.264855 | 158 | 45.014245 |  1.806534 | Bacteria | Firmicutes     | Negativicutes       | Selenomonadales   | Veillonellaceae    | Megasphaera          | NA                                     | TGGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGCCGCGTGAGTGAAGAAGGTCTTCGGATTGTAAAGCTCTGTTATACGGGACGAAAAAGACGGATGCCAACAGTATCCGTCCGTGACGGTACCGTAAGAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGAATTATTGGGCGTAAAGGGCGCGCAGGCGGTTCGGTAAGTCTGTCTTAAAAGTGCGGGGCTTAACCCCGTGAGGGGACGGAAACTGTCGAACTTGAGTGTCGGAGAGGAAAGCGGAATTCCTAGTGTAGCGGTGAAATGCGTAGATATTAGGAGGAACACCGGTGGCGAAAGCGGCTTTCTGGACGACAACTGACGCTGAGGCGCGAAAGCGTGGGGAGCAAACAGG |\n",
       "|  261842 |  1.924361 |   4 |  1.139601 | 11.256905 | Bacteria | Firmicutes     | Bacilli             | Lactobacillales   | Streptococcaceae   | Streptococcus        | mutans                                 | TAGGGAATCTTCGGCAATGGACGAAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTAAGTCAAGAACGTGTGTGAGAGTGGAAAGTTCACACAGTGACGGTAGCTTACCAGAAAGGGACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTCCCGAGCGTTGTCCGGATTTATTGGGCGTAAAGGGAGCGCAGGCGGTCAGGAAAGTCTGGAGTAAAAGGCTATGGCTCAACCATAGTGTGCTCTGGAAACTGTCTGACTTGAGTGCAGAAGGGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCAGTGGCGAAAGCGGCTCTCTGGTCTGTCACTGACGCTGAGGCTCGAAAGCGTGGGTAGCGAACAGG |\n",
       "|  247625 |  1.819876 |  16 |  4.558405 |  9.754440 | Bacteria | Proteobacteria | Gammaproteobacteria | Enterobacteriales | Enterobacteriaceae | Escherichia/Shigella | NA                                     | TGGGGAATATTGCACAATGGGCGCAAGCCTGATGCAGCCATGCCGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAAGGGAGTAAAGTTAATACCTTTGCTCATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGCACGCAGGCGGTTTGTTAAGTCAGATGTGAAATCCCCGGGCTCAACCTGGGAACTGCATCTGATACTGGCAAGCTTGAGTCTCGTAGAGGGGGGTAGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCGAAGGCGGCCCCCTGGACGAAGACTGACGCTCAGGTGCGAAAGCGTGGGGAGCAAACAGG |\n",
       "|  247551 |  1.819332 | 123 | 35.042735 |  2.480154 | Bacteria | Fusobacteria   | Fusobacteriia       | Fusobacteriales   | Leptotrichiaceae   | Sneathia             | sanguinegens                           | TGGGGAATATTGGACAATGGAGGGAACTCTGATCCAGCAATTCTGTGTGTGTGAAGAAGGTTTTAGGACTGTAAAACACTTTTAGTAGGGAAGAAAAAAATGACGGTACCTACAGAAGAAGCAACGGCTAAATACGTGCCAGCAGCCGCGGTAATACGTATGTTGCGAGCGTTATCCGGAATTATTGGGCTTAAAGGGCATCTAGGCGGTAAGACAAGTTGAAGGTGAAAACCTGTGGCTCAACCATAGGCTTGCCTACAAAACTGTTGAACTAGAGTACTGGAAAGGTGGGTGGAACTACACGAGTAGAGGTGAAATTCGTAGATATGTGTAGGAATGCCGATGATGAAGATAACTCACTGGACAGAAACTGACGCTGAAGTGCGAAAGCTAGGGGAGCAAACAGG                       |\n",
       "|  240660 |  1.768688 | 134 | 38.176638 |  2.570635 | Bacteria | Fusobacteria   | Fusobacteriia       | Fusobacteriales   | Leptotrichiaceae   | Sneathia             | sanguinegens                           | TGGGGAATATTGGACAATGGAGGCAACTCTGATCCAGCAATTCTGTGTGTGTGAAGAAGGTTTTAGGACTGTAAAACACTTTTAGTAGGGAAGAAAGAAATGACGGTACCTACAGAAGAAGCGACGGCTAAATACGTGCCAGCAGCCGCGGTAATACGTATGTCGCGAGCGTTATCCGGAATTATTGGGCTTAAAGGGCATCTAGGCGGTTAAACAAGTTGAAGGTGAAAACCTGTGGCTCAACCATAGGCTTGCCTACAAAACTGTATAACTAGAGTACTGGAAAGGTGGGTGGAACTACACGAGTAGAGGTGAAATTCGTAGATATGTGTAGGAATGCCGATGATGAAGATAACTCACTGGACAGCAACTGACGCTGAAGTGCGAAAGCTAGGGGAGCAAACAGG                       |\n",
       "\n"
      ],
      "text/plain": [
       "   ASV.read.count ASV.read.percent ASV.prevalence ASV.prevalence.percent\n",
       "1  2821241        20.734208        307            87.464387             \n",
       "2  1163923         8.554044        140            39.886040             \n",
       "3   803447         5.904790         94            26.780627             \n",
       "4   603155         4.432780        107            30.484330             \n",
       "5   502779         3.695085        126            35.897436             \n",
       "6   444239         3.264855        158            45.014245             \n",
       "7   261842         1.924361          4             1.139601             \n",
       "8   247625         1.819876         16             4.558405             \n",
       "9   247551         1.819332        123            35.042735             \n",
       "10  240660         1.768688        134            38.176638             \n",
       "   ASV.CV    Kingdom  Phylum         Class               Order            \n",
       "1   1.137142 Bacteria Firmicutes     Bacilli             Lactobacillales  \n",
       "2   2.368573 Bacteria Firmicutes     Clostridia          Clostridiales    \n",
       "3   3.209890 Bacteria Firmicutes     Bacilli             Lactobacillales  \n",
       "4   2.535069 Bacteria Firmicutes     Bacilli             Lactobacillales  \n",
       "5   2.550646 Bacteria Actinobacteria Actinobacteria      Bifidobacteriales\n",
       "6   1.806534 Bacteria Firmicutes     Negativicutes       Selenomonadales  \n",
       "7  11.256905 Bacteria Firmicutes     Bacilli             Lactobacillales  \n",
       "8   9.754440 Bacteria Proteobacteria Gammaproteobacteria Enterobacteriales\n",
       "9   2.480154 Bacteria Fusobacteria   Fusobacteriia       Fusobacteriales  \n",
       "10  2.570635 Bacteria Fusobacteria   Fusobacteriia       Fusobacteriales  \n",
       "   Family             Genus               \n",
       "1  Lactobacillaceae   Lactobacillus       \n",
       "2  Lachnospiraceae    NA                  \n",
       "3  Lactobacillaceae   Lactobacillus       \n",
       "4  Lactobacillaceae   Lactobacillus       \n",
       "5  Bifidobacteriaceae Gardnerella         \n",
       "6  Veillonellaceae    Megasphaera         \n",
       "7  Streptococcaceae   Streptococcus       \n",
       "8  Enterobacteriaceae Escherichia/Shigella\n",
       "9  Leptotrichiaceae   Sneathia            \n",
       "10 Leptotrichiaceae   Sneathia            \n",
       "   Species                               \n",
       "1  iners                                 \n",
       "2  NA                                    \n",
       "3  acidophilus/casei/crispatus/gallinarum\n",
       "4  NA                                    \n",
       "5  vaginalis                             \n",
       "6  NA                                    \n",
       "7  mutans                                \n",
       "8  NA                                    \n",
       "9  sanguinegens                          \n",
       "10 sanguinegens                          \n",
       "   ASV.ID                                                                                                                                                                                                                                                                                                                                                                                                                                       \n",
       "1  TAGGGAATCTTCCACAATGGACGCAAGTCTGATGGAGCAACGCCGCGTGAGTGAAGAAGGGTTTCGGCTCGTAAAGCTCTGTTGTTGGTGAAGAAGGACAGGGGTAGTAACTGACCTTTGTTTGACGGTAATCAATTAGAAAGTCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGTGCAGGCGGCTCGATAAGTCTGATGTGAAAGCCTTCGGCTCAACCGGAGAATTGCATCAGAAACTGTCGAGCTTGAGTACAGAAGAGGAGAGTGGAACTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAAGAACACCGGTGGCGAAGGCGGCTCTCTGGTCTGTTACTGACGCTGAGGCTCGAAAGCATGGGTAGCGAACAGG\n",
       "2  TGGGGAATATTGCACAATGGGCGAAAGCCTGATGCAGCGACGCCGCGTGAGCGAAGAAGTATTTCGGTATGTAAAGCTCTATCAGAAGGGAAGAAAATGACGGTACCTTACTAAGAAGCTCCGGCTAAATACGTGCCAGCAGCCGCGGTAATACGTATGGAGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGTGTAGGCGGCACTATAAGTCTGATGTGAAAACCTAAGGCTTAACCATAGGATTGCATTGGAAACTGTAGAGCTGGAGTATCGGAGAGGCAAGCGGAATTCCTGGTGTAGTGGTGAAATACGTAGATATCAGGAAGAACATCGGTGGCGAAGGCGGCTTGCTGGACGATAACTGACGCTAAGGCTCGAAAGCGTGGGAAGCGAACAGG                         \n",
       "3  TAGGGAATCTTCCACAATGGACGCAAGTCTGATGGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTTGGTGAAGAAGGATAGAGGTAGTAACTGGCCTTTATTTGACGGTAATCAACCAGAAAGTCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGCGCAGGCGGAAGAATAAGTCTGATGTGAAAGCCCTCGGCTTAACCGAGGAACTGCATCGGAAACTGTTTTTCTTGAGTGCAGAAGAGGAGAGTGGAACTCCATGTGTAGCGGTGGAATGCGTAGATATATGGAAGAACACCAGTGGCGAAGGCGGCTCTCTGGTCTGCAACTGACGCTGAGGCTCGAAAGCATGGGTAGCGAACAGG\n",
       "4  TAGGGAATCTTCCACAATGGACGCAAGTCTGATGGAGCAACGCCGCGTGAGTGAAGAAGGGTTTCGGCTCGTAAAGCTCTGTTGTTGGTGAAGAAGGACAGGGGTAGTAACTGACCTTTGTTTGACGGTAATCAATTAGAAAGTCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGTGCAGGCGGTTCGATAAGTCTGATGTGAAAGCCTTCGGCTCAACCGGAGAATTGCATCAGAAACTGTCGAGCTTGAGTACAGAAGAGGAGAGTGGAACTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAAGAACACCGGTGGCGAAGGCGGCTCTCTGGTCTGTTACTGACGCTGAGGCTCGAAAGCATGGGTAGCGAACAGG\n",
       "5  TGGGGAATATTGCGCAATGGGGGAAACCCTGACGCAGCGACGCCGCGTGCGGGATGAAGGCCTTCGGGTTGTAAACCGCTTTTGATTGGGAGCAAGCTTTCGGGTGAGTGTACCTTTCGAATAAGCGCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGCGCAAGCGTTATCCGGAATTATTGGGCGTAAAGAGCTTGTAGGCGGTTCGTCGCGTCTGGTGTGAAAGCCCATCGCTTAACGGTGGGTCTGCGCCGGGTACGGGCGGGCTAGAGTGCAGTAGGGGAGACTGGAATTCCCGGTGTAACGGTGGAATGTGTAGATATCGGGAAGAACACCAATGGCGAAGGCAGGTCTCTGGGCTGTTACTGACGCTGAGAAGCGAAAGCGTGGGGAGCGAACAGG                  \n",
       "6  TGGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGCCGCGTGAGTGAAGAAGGTCTTCGGATTGTAAAGCTCTGTTATACGGGACGAAAAAGACGGATGCCAACAGTATCCGTCCGTGACGGTACCGTAAGAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGAATTATTGGGCGTAAAGGGCGCGCAGGCGGTTCGGTAAGTCTGTCTTAAAAGTGCGGGGCTTAACCCCGTGAGGGGACGGAAACTGTCGAACTTGAGTGTCGGAGAGGAAAGCGGAATTCCTAGTGTAGCGGTGAAATGCGTAGATATTAGGAGGAACACCGGTGGCGAAAGCGGCTTTCTGGACGACAACTGACGCTGAGGCGCGAAAGCGTGGGGAGCAAACAGG\n",
       "7  TAGGGAATCTTCGGCAATGGACGAAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTAAGTCAAGAACGTGTGTGAGAGTGGAAAGTTCACACAGTGACGGTAGCTTACCAGAAAGGGACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTCCCGAGCGTTGTCCGGATTTATTGGGCGTAAAGGGAGCGCAGGCGGTCAGGAAAGTCTGGAGTAAAAGGCTATGGCTCAACCATAGTGTGCTCTGGAAACTGTCTGACTTGAGTGCAGAAGGGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCAGTGGCGAAAGCGGCTCTCTGGTCTGTCACTGACGCTGAGGCTCGAAAGCGTGGGTAGCGAACAGG\n",
       "8  TGGGGAATATTGCACAATGGGCGCAAGCCTGATGCAGCCATGCCGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAAGGGAGTAAAGTTAATACCTTTGCTCATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGCACGCAGGCGGTTTGTTAAGTCAGATGTGAAATCCCCGGGCTCAACCTGGGAACTGCATCTGATACTGGCAAGCTTGAGTCTCGTAGAGGGGGGTAGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCGAAGGCGGCCCCCTGGACGAAGACTGACGCTCAGGTGCGAAAGCGTGGGGAGCAAACAGG\n",
       "9  TGGGGAATATTGGACAATGGAGGGAACTCTGATCCAGCAATTCTGTGTGTGTGAAGAAGGTTTTAGGACTGTAAAACACTTTTAGTAGGGAAGAAAAAAATGACGGTACCTACAGAAGAAGCAACGGCTAAATACGTGCCAGCAGCCGCGGTAATACGTATGTTGCGAGCGTTATCCGGAATTATTGGGCTTAAAGGGCATCTAGGCGGTAAGACAAGTTGAAGGTGAAAACCTGTGGCTCAACCATAGGCTTGCCTACAAAACTGTTGAACTAGAGTACTGGAAAGGTGGGTGGAACTACACGAGTAGAGGTGAAATTCGTAGATATGTGTAGGAATGCCGATGATGAAGATAACTCACTGGACAGAAACTGACGCTGAAGTGCGAAAGCTAGGGGAGCAAACAGG                      \n",
       "10 TGGGGAATATTGGACAATGGAGGCAACTCTGATCCAGCAATTCTGTGTGTGTGAAGAAGGTTTTAGGACTGTAAAACACTTTTAGTAGGGAAGAAAGAAATGACGGTACCTACAGAAGAAGCGACGGCTAAATACGTGCCAGCAGCCGCGGTAATACGTATGTCGCGAGCGTTATCCGGAATTATTGGGCTTAAAGGGCATCTAGGCGGTTAAACAAGTTGAAGGTGAAAACCTGTGGCTCAACCATAGGCTTGCCTACAAAACTGTATAACTAGAGTACTGGAAAGGTGGGTGGAACTACACGAGTAGAGGTGAAATTCGTAGATATGTGTAGGAATGCCGATGATGAAGATAACTCACTGGACAGCAACTGACGCTGAAGTGCGAAAGCTAGGGGAGCAAACAGG                      "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "as.threshold$ASV.filtering.stats[1:10,]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll use the same plotting function as above, __plot.threshold__, to visualize the effects of multiple AS filter thresholds on the ASV count across the dataset. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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SZE6MJu2bJly5Ytq729Q4cOM2fO3Lx5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\ngcQOAAAAwEAgsQMAAAAwEP8PHWu5mQ0Rk7UAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot.threshold(as.threshold)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Generally, I choose AS filter thresholds by examining the values around when the taxonomic curves begin to become asymptotic. Filtering at those values should remove most low abundance, low prevalence taxa (which we can't do too much with, statistically) and/or minor contaminants or stochastic associates. <b> With that said, each dataset looks different and hopefully these tools can help guide you to a logical solution. </b> <br>\n",
    "<br>\n",
    "\n",
    "Now that we've taken a peek at the effect of multiple thresholds and filters on the dataset ASV counts, let's see how these filters will affect the taxonomic profile of our ASVs. We can again use __plot.threshold__ to visualize these effects. For this purpose, we'll have to specify a few extra parameters, as illustrated below. For each plot, either a solid (x-axis variable) or dashed (y-axis variable) black line indicates the assocaited filter threshold chosen. __Taxa that would remain after filtering exist in the space above and right of the horizontal and vertical lines, respectively.__ <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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vVHhY0ETyYgEoQQQqgJEj3cyZw5c2644YbLL7+c/rlhw4bnn38+tsDf/va3kpKS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Lly97eHjgxXIAoFevXqhWTJmZmQm11hln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\njR0AAABAO4HGDgAAAKCd+H+mWim5NALXCQAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot.threshold(est.obj = as.threshold, x= \"P\", y= \"CV\", taxrank = \"Phylum\", PFT = 2, CVT = 0)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because __plot.threshold__ returns a ggplot2-class object, we can modify it to accomodate various graphical modifications. In the above figure, the number of phyla results in truncated facet labels. Let's modify our next plots to be a little more readable by moving our legend and reducing the font size of our facet labels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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5O0AGa7UFiSaiNSjC7VAQAQ0lQ4QnQACBx6zZTZ3VJ4jlr7rRY4Hjj0T6JxRCpE\nV4hUL9jweTeCJAxJqTtWu9EbPEKInmk/o0v+bzNsXVJtVLsjlYHdvn37AOCmm24KTSwtLY1y\nSGZmZqPfc4qiOJ3OSOnGx4KCgqVLlxofP/roo4aGhpycHPrR7/crimKxWMxmMwCYzWbjq0jo\nuu7xeGJmC8Xj8ei6brfb2V/pUBRFkqSsrCzG/IQQ+jMxMzOT1oWFYDCo67rD4WDMr6oq/dGT\nnZ3NPt7u8/nMZjN73WP+cBcEIVQpqggAmEwmCBGRKIGGw58mM6oToj7Yjf5t+EPMA64kJqso\niqF9ODpUeqfTKYqsi1P6fD5VVS0WC5f0fr8/OzubMT8wjFuYzWZDLLlhf82OF4LHPtUDx+Xq\nxu+0NkHw7ni8OU/VbY6cjCxWF47bGR0Oh8USfkZgU3idUdM0OjzPKz2XM7IMWoQ6o1H3Rs4Y\nHb/fL4qi3W5ntCq+C5HX67XZbOyKSJIUDAa5nBEAXC4XlyLGPYhLep/Px+WM9AoZhVBnBIBA\nICDLMk2EWDrKivvrPYt2H3mB6KqRKAhCn27Xjxi42GGPuEiF1+vVNM1ms3FJHwwG2Z0RTo+i\ncTmjJEmapiXbGf1+v8lkSrAzMp4rGdDH8KtXr2402PbVV1898sgjxsfbb7+d/nPLLbcUFBQo\niuLxeAwfq6mpKSkpiZRunMRmsw0fPtz4uGXLFrfbbQhMNRAEgf4jimJM7ekTcfYuQs/PeHID\nXdcFQWDPb0wHMZlM7EfRjsJVF4rZbGbvvoIgcFlFH+JEJ7QxjTkKjURUqvcQjXssnRFbv0vl\nw1uIEggfwAkiAAj2HBJwscYfgihm5NpGzA0CxCG92Wymt1Kmovg7JCWOrhLdDFEUzWbx5Jf3\n1Wx/gugaCAIQwtBgzQrWBZPDZM3ickbgqXvLOKMR0PBKz2UVywSg0I5kTAPi6mOiKHL1RqOF\nLRYLe2AHnIrQp5BczkhJtjPSQ5LhjMY56a9rljujL3hszebR9Z49jdIJIZVH36iq+XTChRvy\ns8OP2sRRdyp9HHXnlZ4Q0gLOyFV3JmdkPFcy6NmzJyFk//799CMhZN68ea+99tqIESPWrl27\ndu3alStXAsBzzz1HP44dO7asrMxsNu/YsYMe4vV6Dx8+PGTIkEjpKakX0qogQb7pDlzYB15Z\neOtG55hF9n6jTdldBFOIcwqitei8/BlvFM77SCw6nyZB9NuPIIq2rNwp/6NCgzMAACAASURB\nVE9wFCTP5tbJz/+ZUf3NYqJrANAyD80tHc5pgVIQJO3Rifrh1gkNnr1hvyVA/NKJ9z+/Qla4\nJx0i8ZHKEbuzzjqrpKRk+fLld999d3Z29ttvv+3xeMaNGxflEKfTefHFF69ataqoqMhmsy1d\nurRHjx5DhgwRRTFseovVBWm1CI4kTqKydjtbzCxwDJsGw6YBABBNrT6geU6I1ixTYbGYcept\nHvPYJ2wNB7QDHysndpOgW8wsJGpQrfr+VBxzGlvxBc4xfzLlniFzTu9t68juIw373m7ZMgXn\nkEdi50IQJBZ7j7x8sm5blAyE6B7/ke37lpw78K8tZlV7JpWBnSAI999//4oVKxYsWKBpWklJ\nySOPPJKXlxf9qDlz5rz00ksLFixQVbWsrOz++++no8SR0pF2jrR/Q5LOLGZ3E52dfpUkmMwd\n+5s79m+a2dR1sKPX8NAU3V8vH/xMrf+BKJIpp6uteJQpL5nrHrdaiC7V7xYEkbTgO8tmZy9L\nTr8WKw5B0pidh14QQCQQzX8FEHYdemH4mX8RBLwvJ50WDezsdvvatWtDU7KysubPnz9//vyw\n+fPy8hrlBwCr1Tp37ty5c+cypiPtFqIpDW/NlQ9vTdL5naMXNOdw0ZFnH3R1ooxpuyi+o0SV\nWjKqAzDWSEEQpFloWrC6/r/Rozo4/UC2wXsgz9ne3/dvATB2RtILohNVAgDQVc8HC5MX1YEg\nkiD3Wk1IU1R/TcsXqgdSUCiCpB9+6QT7rzJ/8FhSjUEouA02kibovhr9y+dJ5X+UQ7sAQDqw\nKbBrX3NOKNqydCnKOs/Evf4BosiO4TOaUwpC9GS9sxwFwRZjygeCICxYLRxrfnFlRuIGR+yQ\ndEA6uLn+H2PJjrcgcaNouhT1DQZCAMCz8TH1ZLPCR0S0ZLZ0kYJoLRza0oUiSDpis+RmZZwh\nMExuMIk2fA7bMmBgh7R55B+/bnhrHlECAIldKYPpVL6tS2NnQiJjcfZo6SKJ7ug1JXY2BEEY\n6NdzasxlJwUQene72mxiXewXaQ4Y2CFtG6JK7rULhFTtA0t06cCnp2b1IXFhsuaYHR1jrPCX\nULK6X2zvNqbFikOQ9GZIv7ttlrwor7sKgiiIluFn/qUlrWrPYGCHtG2Cuz/Q3Mdb+p3KEIga\n1FxVqSo9PbAXnNVyhQlC98v/2XLFIUi6Y7cVXn7eW4JgFsJFFAKIAGT0sOX4HLbFwMAOadsE\n93/SkoM94VGDKTagjSNanS12LRJAMNsLW6YsBGknnNHpkokXbcpy9AAAY+iO/mO3FY4buaak\n5/RU2tfOwLdikbaN+mN5y+xAFRlBdEbc3xphQarfBz1ib4CYEMyOzoBLpCJIoulSMHLa2H37\nf/zn/iPv+OUjhKg5WX16dr68pOd0izkr1da1L9ppYEcI0XWd7u4Mp7espon0o/FVJGjOmNka\nFcp4cgNN0wgh7PmNXbE1TWM/Std1LqtUVTX+Yd97mxDCZRXLVsdqw896nofxhElBEE2F/TRL\nlha1Xrx1Nzokr/Sqqhr7rzMeEof0XN0+9jkll1S/O4EnjIro6H4p3dsb0sIZDTfhlT7hzhhq\ntlF3rnbmvagaVimKkrwLURzOSEm2M9LqJ9YZm31nFIq73tAh64rs7OxfFCExjGwBZww9sD04\nYzsN7FRVVVXV7f7VnsSKotD7VtOvIsGYjUK7ryRJksQ3156rFIrf7+fKTwiJoxSPhyOoIoSo\nqspedxJrHI4QXas9BL3YTUgCRCdnXhOz6Qghfr+f694DALqu84ri9UZZeC98KYqi8HbjOLp9\nFPxVW9jeP04IxNJrutvtNpxRlllX0aOHxOeMvNLHUQqv9Jqm8V6IohP2sklvQoxXVEKIIAjs\nihjwXogCgUAgEOAqop04Y9g7I00EnjsjryIAIMsyr/RxuEkc0reAMwJAHN0+Cu00sLNYLFar\ntaCggH70eDySJFmtVqvVCgChX0VC07T6+vqY2UKpr6/XNC0jI8PhYH3lW5KkQCCQm5vLmJ8Q\nUltbCwBOp5PWhQWfz6frutPpZMyvKIrL5QKAvLw89g15XS6X1WrNyMhgzB/T/bTqA6me3CZY\ne56bd96NIJii56uvr3c4HDabjfG8Pp8vEAiYTKaYWycbUOlzc3NNphjGGLhcLkVRbDYbl/Ru\nt5ur29MOGe2c7soW2+GrYPDvO/cdDSHOmJnJuoqeJEl+v59XEQBwOp1c0nM5o6qqDQ0NAMAr\nPZczBoOxHS30sqnrel1dHQCYzWZgu6ICgMfjEUWRXRFZlulNNz8/nz105nVGv9/v9/u5nBEA\nampquBRxu92yLHM5o6qqLpeLyxmpKFFodGf0er3BYJAmApuOVHouRRoaGlRVtdvtXNL7fD5e\nRQAgKyuLS3pN05LtjG6322w2s0cFLM6Ic02Qtopa90PqChcBwNKtLGfSszGjOiQ6REv+zhOC\nCAA5/W7o/Ju/Jb0sBEGQlNJOR+yQdKAFAoJI2JxZ589xnDNDMFlSZkP6kPQHsdas7h3O/Uve\ngBktNjSIIAiSKjCwQ9oqYnaXxJ9UEMMudGzpNCBr9D26t1pVlYAlX+hYmtmhU+JLb6ckJdjK\n7T89s9tFgslqyy/N6HA2hnQIgrQTMLBD2irmjv0Sdi5BFK2OrIsWeD9/RvfX0Sd3AgAhOghi\nxuDJzkvvFSwZACBJUpBnXjASmyQ8y87te133S1diMIcgSDsEAzukraKe2JOYEwkiCJB99VO2\n4gvsg8ZL+zfKP5brnpNCRra5Qz97/8tMeT0TUxASDpbtw/lOKFq6X/5PjOoQBGmfYGCHtFU0\nz4mEnEfIyM29+klr0XkAIFgd9oFX2QdelZAzIywQogMkbtBOEGz5pRjVIQjSbsHADmmrCGZ7\n809iLh1vu+geay7uMZUuEJLd++pUG4EgCJIyMLBD2irm/ASsTSzm96aT55BUISRyjp1gsmQV\nnPX7xJ0QQRCkjYHr2CFtFXOHPiA2+5cJrkKXcoRELXciAEC3S18yZeD4K4Ig7ZdUjtjNmTPn\nuuuuGz16NNdRmqatXLly06ZNkiSVlpbOmzevc+fOABAMBleuXLl169ZAINCtW7drrrlm1KhR\nyTEcSR+E3DNSbUJ7h+iJmWMnmmzdLlmRXXxN80+FIAjSdklBYKdpWlVV1bp1644fPx7H4S++\n+OK2bdsefvjhwsLCl19+edGiRc8//7zNZlu2bNmBAwceeuihDh06rF+/fsmSJTabbfjw4Qm3\nH2klKD9XgK424wSCYLGZug9LmEFInGgAzVrnWbA4Moqu737+A1YnhukIgrR3UvAoduXKlbfd\ndtuHH34Yx7Fut3v9+vXTpk3r0aOHw+GYNWtWTU3N119/7fV6N2/efOONN/bo0SMjI2PSpEm9\nevX66KOPEm480noIfPNq805AHMNnQyLewEBSiCCY+s04mj1ssSWre6ptQRAEST0pGLGbPXv2\n7Nmzg8HglClTQtNlWV61atXmzZt9Pl9RUdHkyZNHjBjR6Nhdu3ZpmjZ48GD6MSMjo1evXt98\n802nTp00TSsuLjZy5ubmKoqS7LogKUQ5vqsZRwuWzmdmnj/XG8BO0pYRxMzuF4rWbPDVp9oU\nBEGQVkEreit2yZIlfr//0UcfzcnJ2bJly+LFixctWjRkyJDQPMeOHbNarbm5uUZKXl5efX19\nv3791q5dayTW1tbu2bPnpptuMlLq6uoef/xx46MkSQDgOb2FgKqq9K/xjyfW7gKEkNAzsKDr\nOgDIsqxpGvshuq5zlUIJBAK0jizQWrOXQisCAD6fj90kTdMkSaJlMeaPkSHgYi+9EaZuQ8xj\nF3sDCrXHqBG7VbzSB4NBWWbd3Nawild6n88nCKxLuNG6KIrCKz2XVdRTkgXRM0v/D+2HXq+X\n/TjDGdml53VGo+KBQIBX+jhK4ZU+sc4IES6b9ECWKyqEdHtGq4ycvNJzOSOtQrKdkf3WYxDH\nPSimM2qaFmoDtYomMppHi+BShLZwUp3RgFd6QkiynVFVVV3X2aMClpytJbCrrKwsLy9fvnx5\nx44dAeCyyy4rLy/fuHFjo8AuEAhYrdbQlIyMjJMnT4amHDlyZPHixaNHjx4zZoyRGAwGN2zY\nYHwcPHhwVlZWo9CH9hX6D2NUxB48GRjhIztxlBLHaCV7xzLgNUzXdd66R0HQ9XjmEuT3FQff\nAH0ulQURTtvfAnWPQxFCCG8p7NcsA/bebhBHh0wSjn43C/nn0lrHYZWmabzSt4zLx9EheaVP\nrDNChI5Eb3Vcfaw9O2PLdMgo0JtgSu6MLVP3lrkzptwZW0tgt2/fPgAIHWMDgNLS0o0bNz7z\nzDP044IFCzIzMxtpqSiK0+k0/n/jjTfef//9WbNmjR07NjRboxcpzGazIAgWy6kp25qm6bou\niiKNskO/igQhRFXVmNlCUVWVEGIymUSRNRyhHmU2c8hEOy6tIOMhtOOaTKxvJtK6AwBv9UVR\n5Kp7DDOYT3UK0WIZ+7ip6PzQNN66Gz+tuOquKAqX7rRDxlEKl+60QwqCwN7B4uj2SZkRIQhA\nwFl6a87QBwXBFLdVoijySs9eiuEmvNJDXM7IK31inRGaXDZpC7NfUaGlLkS8zkh153IT4HdG\n4x7EW33ei3D0DIIgGGK5fZVHjr9b596h6t46z35qZvLujEl1RjjdIVvGGXmrLwgCV91j5mkt\ngR31nNWrVzcakAOA0PVQPv/8c/rkyAjmampqSkpKAKC+vv6hhx5yuVyPPPJInz59Gp2koKBg\n6dKlxscnn3zy2LFjOTk59KPH45EkyWw2Uz0sFovxVRSD6+vrY2YLpb6+XtM0m83mcDgYD5Ek\nKRAIsJdCCKmtrQUAh8PRtCUj4fP5dF03mjQmiqK4XC4AcDqd7E7icrmsVmtGButqwIFAIHoG\n0ZYFwDHgb+lSmj94XKNEj8cjimJmZibjSSRJoiPzvNI7HA6bzcaY3+fzBQIBk8nEK73T6WS/\nQLhcLkVRrFYrl/Rut5ur7rRDJhZBtPaauNHR5VSMTp0xOzub/T5qOCOX9H6/Pz5n5JKeyxlV\nVW1oaAAAXum5nDEYDMbME3rZ1HW9rq4OTt8UWa6owO+Msiy73W4A4JWeSxG/3+/3+0VR5Or2\nNTU1XIq43W5Zli0WC5f0LpeLyyoqShToTdCRaf684o49R14iRBdABAH8QQIAVbUbf65bXdrr\npihnoNJzKdLQ0KCqKpczyrLs8/l4FQFOZ/T7/ZqmxeGMWVlZXNKbzWb2qIDFGVvLAsU9e/Yk\nhOzfT38WACFk3rx5r732WqNsZWVlZrN5x44d9KPX6z18+DB9XLtkyRJZlv/2t781jeqQtEQ0\ns3oCRfn5O/9/X1GqvgfCPbSOtCqIJgkmfJ0ZQRKPTtR3No3affhFQnQAIKATogPQR+rKJ/+9\n+Yvv70m1jUgMWktgd9ZZZ5WUlCxfvvzo0aNut/ull17yeDzjxjUeX3E6nRdffPGqVauqqqpq\na2ufeuqpHj16DBkyZP/+/Tt37rzrrru4QnikTaPL3DNnPR8/XPfytdXPnO/78gWicc+AQVoP\nsvtQqk1AkDSkun57dcP2KBm+3fd45U9vtZg9SBy0lkexgiDcf//9K1asWLBggaZpJSUljzzy\nSF5eXtOcc+bMeemllxYsWKCqallZ2f333y+K4u7duwFg/vz5oTkHDhz4yCOPtFAFkBaHSN74\ndizQAw3eTU9I+zbkTlnWzKVxEQRB0gZfoMoXOBo9jwDi1u8X9O4+SRRaS/yANCJlwtjt9tAF\nSgAgKytr/vz5jYKzplit1rlz586dOzc08eqrr7766qsTbyXSmtG0OLeiIgQAlGPfuf71e/P4\npcD7EgbSCjA7OqfaBARJN2pdO2LmIaB7/D8eq9nSrcNFybcIiQe8pSFtFcI6NzfS8UT+6Rt1\n17uJsQZpWeSGfak2AUHSDV+wijHnibptSbUEaQ4Y2CFtFaH5I22CqFa8nghbkBZG8B39LNU2\nIEi6oap+xpxBOfFvuyOJAgM7pK0imFnfWo8I0fWGH3XPsUSYg7QgAig+1qEFBEEYMZtZFxzJ\nsHVIqiVIc8DADmmrEEjQXlXe6sScB2kpBBBN1uxUW4Eg6YYzoztjzi4FI5NqCdIcMLBD2ixq\nYtYrISZ8MbaNQYhmLzwr1VYgSLqR5ejBki0ns3en/HOTbQwSNxjYIW0Vwr+FXxgEkyn3jASc\nB2lRhOw+16baBgRJN/xBpnkpBbmDBAGDh9YLaoO0XZr9KFYQxTOGgzUrEcYgLYaQWzLVXjAw\n1WYgSLqhqAybNApwvOarBFx+kaTR3hcYJC6XVr7FvHunpaFeEEX98EEAAIZNdpG2jwCEWM+9\nOdVmIFwItrz+XS9aGjsjgiCcyCrDdj4E/NKJgFSdYeuYfIuQeGjXgZ325efqB2tAVURBoIvW\ngt8HAPr+Pfr+vWK//im2D0kiAgDJGnW73hmnarUlMntc0uPyN0V8cwJBkgDdH5YFSXFhYNdq\naaeBnaqq2onj6prVIAgAp7YiADg9uqxpyopl8uSpWp+S6OdpaGhgL1TXdQAIBoOyzDrrnxCi\n6zpXKRSfz+f3s65IpOs6IYS9FHK6udxuN7tJmqZpmiZJErtV7CfnQwAA0TTiFmXQNE2WAUBR\nFMZDjbrzSu/z+QKBAHt+ANA0jVd6t9stCKwLN2uaBgCyLHNJz9VVIKTFEkLehW95AgCBXxlA\ni3C5XOznoXWXJIld+rjdhFd63ham8ErP5YwsIiqK0tRs2s5hvwprlSAIcTgjr/R+v5/XGeO4\nDns8HJtZx+GMAMDbVWJeVAWB9U2y2rqjoEZc8STZzhj3nTEO6eNweV7pVVVljwpY7oztNLAT\nfV6h5iR0zYOwFywCAIL1vbfhzoWQGX4Clq7rqqpmZGSwF+rz+QghFovFarUyHkL1Zi+FEOL1\negHAarWazaziSpKk6zp7KfTKCAB2u539XuL3+81mM3vdY3d05qJ/dZDJah00yTZ0mpjbAwCC\nwaAgCDYb65J4iqLQyxCv9Far1WJhvWhKkiTLsiiKvNLb7XaRed1mv9+vaZrJZOKSPhAIcNWd\ndshEYbdbBaHxPnI0bubqjT6fT9d1s9nMJX3czsglPSHEbrcz5qcXIgDglZ7LGVnuuKEdyag7\nNYmxjwUCAVEU2RVRVZXepHml57o8yrIsSZIgCFzd3uPx2Gw2dkUCgYCqqmazmUt6TdMS64x2\nay7ADyyn2vzd9EkXfWW3No7tjAsR161B0zQuZ1RVVZIkXkWA884oy7Ku6+yKGHdGXum5uj2L\nM7bTwA5qawCizv4kOiiS6ast5nETwn6vaZrP52MXAwCo5CaTiesoRVHY8xvXU97wkTe4of9Y\nrVb27hsMBrlcN0kjdqacLrnj/mJ8pPETlyLBYBAAeKW3WCxcly0A4BKFSm+1Wk0m1v1zg8Eg\nDey4pA8EAlx1T2xgp578IqvHJY0SDWfkupdACzojl/S6rvN2FQDglZ7LGVlG7EL9yHBeqgij\ni/E6oyAINLDjlZ6r7vSHHJczAoDH4+FShI6e8sa1wHkh8vl80TNYLTmsp5Kqvtn3l4uHvdAo\nnUrPpQgVkcsZBUGQZZlXEQCIQ3ouReiFhVf6xDsj47nSjYAv9js9BPSKb1vCGCQ+4nnGJwh2\n1isX0goJ1nyXahMQJG3pkHu2xZxFZ6vEgJC9P7wsyfXJNwrhpp0GdiTWD5dT2Vz1wPzkG2kD\nCGDuVJpqI5D4ScA+cgiCREAULQW5gxmXMtF19ejJT5JtEhIH7TSwA5V1bVsis84vRtoAhNhL\nx6XaCCR+HF1HpdoEBEljSJ1rF3tuj//H5JmCxE17DeyYX+oWeJ7iI60cyxlDrT1xJ5w2TEbh\n4FSbgCBpS4Nnv6xwvGpqEllnciMtSbsN7FinZzE+tEVaP4Io5k56LtVWIAiCtFLqPHuZJtid\nJtcZY0UwJCW017dikfZH1gV3ipkFqbYCQRCklRKUqpn3ChNslpyuHS5IrkFIXLTXETvmN7EF\nM+sCVEirRhAcI3H3sLZOPCsXIgjCiKazvyxIhg64Fx/Ftk7aa2DHvFAGwVtJWmDO64lhQVtH\nANaloRAEiQP2dezyskvK+t2ZVGOQuGmvgR3zLV5wZCbTDqSFsPa7KNUmIM0HQ3MESSJWs5Mx\n52XnvikKOJWrlZLKwG7OnDkbN27kPUrTtBUrVkyfPn3KlCkPPPDA8ePHG2X4+eefp0yZEseZ\nw8O84yrSmrEU9ku1CUizMbGuUoSkFk31+xq2u6s/UxWOPUORlCOyPVrNsHUszMX301svKYi4\nNU2rqqpat25d05iMhRdffHHbtm0PP/xwYWHhyy+/vGjRoueff97YjkPTtL/97W9006dosL8V\nGwgImTho1+YRc7qm2gSk+eCIXWvH7zlYuf3+40fe1nUJAOpPAAB46iqkwHFbRucUG4fEwh+s\nYskmKfW6rogiTkBvpaRgxG7lypW33Xbbhx9+GMexbrd7/fr106ZN69Gjh8PhmDVrVk1Nzddf\nf21keO2110wmE/sGpjERHBzbDCOtFku3slSbgDQXkbTXqSNthBM/vrtlzaCqw6/TqM7A7z28\nZc3A+hOfp8owhJGgxLRFmK4rvuCxZBuDxE0KRuxmz549e/bsYDA4ZcqU0HRZlletWrV582af\nz1dUVDR58uQRI0Y0OnbXrl2apg0efGoQOCMjo1evXt98882oUaPot+vWrXv66afnzZvX6EBZ\nlg8ePGh8DGqsz3QUn1ewhlmjmG51bOzAzQLdu1fXdfajNE0jhLDnN7YH1jSN/Shd17lK0U63\nnqqq7DE0IYSr7sY+4glBAxOEK5rXqtC6s5dOCOFVhB7FKz3tMFyHxCE9V90TCAExbNGGM7Lv\nO55+zsgrfcKdUQpUV3w6BYge9nmIKtf/9z/jho/9IjNnQKKsCnVGLumT7YyGeW3OGTVdAmB6\nGitJngxrm3HG0APbgzO2osmPS5Ys8fv9jz76aE5OzpYtWxYvXrxo0aIhQ4aE5jl27JjVas3N\nzTVS8vLy6uvrAcDv9z/11FM333xz585hBvxramqmT59ufCzLzc6xMA0j+47+pAoR38VraOBY\npJsSDAZjPyludik+/nWVZf5dcd1uN1d+VVUDgQBvKQmhoSGaqZLEvXEcryh+v9/POV9T13Xe\nUngVAQBZlnmlj6NDJgRiFqIU7XJxT+eSJIlX+jjqHof0bc4Zia64674FopMIm/oQouuqf8fW\nm/uP/CD6qeJwRl7p0RkjwxqO1DdUg9Yp0rfojFz5FUXhjQqi01oebVRWVpaXl99xxx1du3bN\nzMy87LLLzj777KYvQAQCAav1V78nMjIy6OVp2bJlffv2HT16dGIN0234KDYtqKtMtQVIcxF0\nfHmilVL98zpd80eK6igEdG9dua/h2xazCuGHNbCTlOqk2oE0h9YyYrdv3z4AuOmmm0ITS0tL\nN27c+Mwzz9CPCxYsyMzMbBTUK4ridDo3b968c+fOZ599NtL5CwsLV61aZXx8e+HdDTLTyGdW\npkMMGSA00HXd7XbnhvsqEm63W9d1u91ut9sZD5FlWZIkp5P1FXRCCP2plJmZaWEbkgSAQCBA\nCHE4HIz5VVX1er0AkJ2dzf4o1uv1WiwWG/Peu3H8cI9Chlxjyx3WNN3v9wuCkJHBGr7Lskx/\n8PFKb7fbG/0miUIgEJAkSRTF7OxsxkOo9LyKqKpqtVq5pPf5fDk5rItdQVy/3SNBVCFss1Nn\nzMnJYX/6Q53RZrNxSR8MBnkVAQCHw8ElPZczaprm8Xggyc4Yc9Ci5ujHjK+2SJ4vuhVdHPYr\nXmdUFIU+muCVnssZ6TMWLmcEgIaGBi5FfD6foihczqhpmtfr5XLGOAYRI5GdXZAoZ/R4PJqm\ncTmjoiiBQIBXEeB0xmAwqOt6sp3R5/OZTCauqCBmntYS2GmaJgjC6tWrmzZ66CDc559/riiK\nx+MxYp2ampqSkpLvvvuutrb2xhtvNHI+88wzL7zwwhtvvEE/Wq3WAQN+mdvxk9uzt9514+FD\nADCpf99rSvrQ9J+9XgDYduz4je+tp+lmURTN5tWrV69evZrmufbaa6+99lr6NP3dd99tlE7/\nb5ofAARBWLt27YcffmgymVjyA8Bbb721evVqGqIx5n/ttdcAwGKxXHfddTHz03T6dP+GG25g\nzK/ruqIoEyZMmDlzJu2+0fPT/6+44oopU6aYzWbG/BMmTICoSCr59mjw5n8eA4Dxg7KuGniq\nSxxzqwBAvzLSTUQJK5YgCO+9997atWujG2Oka5q2du3a9957j94UWURZvXr1a6+9ZjabRVFk\nzP/Pf/6TesSNN97IKAoASJI0derU6667jjG/oihXXXXVtddeyy7KpEmTLr30Uvb811577cUX\nh7+LGxw+AQer4a6XAAAuK4MxZ59KP+kCANjxI9z1kpEumqM649tvvx3TnlBn/OCDD2hdGJ3r\nrbfeoheo1uOMhBBZlidMmDBjxgx6YUmGM1599dWR5KN4PUf2HSKPLAUAGHUOjDrnVHptPQDA\nvkPwyFIYdQ5cMFyU/T+FFRH4nVHX9RZwxjfeeIPOGEsDZ4z5ROv4UTj+E6x4CgDg7BFw9nmn\n0hvqAAB+qIQVT51Kz3P2CasjnQGWbGdcvXr1m2++ye6Mq1evfvXVV4HTGelUuWQ745VXXjl5\n8uQEOiO0nsCuZ8+ehJD9+/cPHDgQAAght9xyy6hRo0JjNQAoKyszm807duwYOXIkAHi93sOH\nD99www3Dhg27/fbbjWzXXHPNrbfeGqUT1wWCVV7f5wcPAsCAwnw4Hdh5ZBkAqry+f+2rpOmC\nTgBg165dRrOWlpYazc2bvnfv3nfeeYc9/549e9asWcOef/fu3cZlceDAgVx2nnXWWVz5S0p+\n2f6ZJX9xcTFX/n79Yqw8p+rkuFvbetADACUdrVcNPJXulXQAOO5Ww9FuagAAIABJREFU39/p\nMdLF7G67dq2L1Mi8IhqNzNgZ3nvvPa787777Lv2/rKyMS5Sysl9e/mXJ37dvX678/fv3v/TS\nS9nzl5aWxgzsGnxwsgG+PAgAUNwZxpxO9wYBAE42wMfbT6WbHbYo5e7evZtXR6OdGZ2RS8d2\n5YwETLX1QN9P69H1l8DOHwAAqK2Hz7dBj65AgAiCOUqhrdAZjSt2GjhjzMDO6xEb6k7p2Lk7\nnP6RBcEAAEBDHWz/8lS6TuQo5SbbGXfv3s2rY/txRmg9gd1ZZ51VUlKyfPnyu+++Ozs7++23\n3/Z4POPGjWuUzel0XnzxxatWrSoqKrLZbEuXLu3Ro0ejFyxYyM+wd83KLCvpAwADCn/ZGN5p\ntQJA16zM87p1oemE6ALAmWeeaTTxmWeeaeTnTe/fv/+kSZNoLM+Sf8CAAVdffTUdsWPJX1pa\nOn78eACwWCzsdtJBAvb8dMSuf//+XO3Am3/AgAGhC9k0xSwInbPNpQOdAFDS6ZeB3iybCACd\ns83n9Mgw0i3dBp955g+RGplXxPHjx9NBAsZGmzBhAh0kYMw/ceJEOmLH1dkkSSotLWXPH4eI\nXOdvlB6J3EzomAvFZwMA9Al58SnLDgDQMRfKep1Kt2j5Uc4feh1k1HHixIn0hzKjM06YMIEO\nErQeZ6SDBMl2xtLS0vLycoiMM7tPQd6BrucAAPTs9ks6XS2qIA9K+0DPbgCEZOb0i1JoK3TG\nSZMm0RG79uCM2TmW3Hw4uyMAQJfuv6TbMwAAcvOhV8mpdIs5K8r5k+2MpaWlXM545plnxuGM\ndMQu2c4Y+iwxIc4IAAL7S7mJhS53cscddxi/Ibxe74oVK7788ktN00pKSm666aaePXs2PVCW\n5Zdeemnz5s2qqpaVlc2bNy8vL69RnpgjdksmjT8ekB45q6RR+nXvrnvvwMEJfYvfnHgqpjTP\nutnUf1DTM2iaVl9fX1hYyF7l+vp6TdMcDgf7M3tJkgKBAPt0LkJIbW0tAGRnZ7PPJPD5fLqu\ns8/kUxSFTh7Kz89nn0ngcrmsViv7LIpAILBw4cKtW7f+9re/XbJkSdMMRx7s/+R/7feNaPxm\n3+zXqtbt9o4rzVpx4y+LEne6d1/YUjwejyiKmcxrUEuSRGdR8ErvcDjYpzT5fL5AIGAymZr2\n7UhQ6fPy8ujPBhZcLpeiKDabjUt6t9tdUFAQO+tpamtrH3zwwa1bty5evDisS/55ZvcTbvvt\nvz3YKP1/l8PG72H0WfD06Zm31vy+/W7c3/QM1BkLCgrYp/VQZ8zIyOCS3u/38yoCAE6nk0t6\nLmdUVZVOHuKVnssZg8HgPffcE8UZTxzdsOCueVPHNhbxr8/DF9/AyKGw6Pc0QRg1aW9mdvgh\nB15nlGWZThrjlZ7LGel7lFzOCAA1NTVcirjdblmWuZxRVVWXy8XljHV1dX/5y1+2bt3617/+\ndezYsU0z3HLXgJPHlN9ObKzj8ifgu69h8HC46W4AAFG03jIpIAhhLv66rtfV1XEp0tDQoKoq\nlzPKsuzz+XgVAU5n9Pv9mqYl2xndbrfZbGaPCmI6I6RwxM5utxtDo5SsrKz58+fPnz8/+oFW\nq3Xu3Llz586Nkudf//pXAkwEAABTDscceQRBkkdGfpjXX5DWQH6nC03m2Hfl/E7nR4rqkNYA\nAabVQwnRwkZ1SCsBtYkByc5PtQkIggAA2DtyT7pAWgZFqtO12K+x+z1HdJ17VTCkxWB8gkeI\n5vX/nGxjkLhpr4Ed4yixIAjMA6QIgiQVqWZbqk1AwnPix3cIib2AVNB/tLZqQwvYg8QL634/\nde5dSbUDaQ7tNbBzMD3LF4r7soaASKsGRUwHMoouS7UJSHjqj29h9LK6458l2xgkbgRgnRnm\nzOyRVEuQ5tBOAzuxa7fYmQTBMnZ88m1Bko+QmjeEkMRSUDI71SYg4ZGCx1myCYIoB5hyIinB\nbGZ6QiUIpjwnzpVsvbTTwE7o2BmysqLnMV0wWuiOP0paL+xvXQki6wvCCILEgdnKtP8BIYQx\nJ5ISLCamwK5j3tB2Gzy0CdqrNoIgntFTLKHrx4SJD0znX2i+/MoWNgrhQshiXXBEMGNg13oR\nTKyLbuiKN6mWIHHjzDuLbZtR4swvi50LSRFdO1wQO5MgjBm+KnY2JHW018AOAEwmy6x55inT\nhM4hi6IKAABCUW/z+GuAeYU2JCVkDprEmFOw4SBB68WUwRqga8HapFqCxE3nnpNjZxIE0WTv\neAbOb2m9OB09c7L6RM9z/llLcvA5bOumtew8kRoEwTR0uGnocE/Vz2r1SYvNJu79AfYfFGI9\npUVaA7bB1wCsZMkpOjkWE0ZaGEFkvQqZ7BxrsSItSWZOSUZmT4DGC9v+CkJ6D/yD1Y7O2Kop\nyBk0YtCF5TsXEaI1/k4QR5/zwoAinOra2mmngZ2u67quS9KphZf0zCzNahPMZl0Q6LfGV1HO\nAAAxs4VClwjSNI39KFVVCSHs+Y1ViBRFYd9TRNM0liqH5qf/yLLMPtFN13VVVbnqzpgzJqau\nQyOVq+s6VwsrikL/4ZXeOJAF2sJxSC/LMvteILQPc3VIahhX3WMiWpwAx2JkEkRLTj9Ft0C4\nog1nZO+NcTgj9an4nJHxEGoSVym07sAvfcKdMTNnYFZujbfh+0gZ8juP7t7/D1EK5a27YRWv\n9FzXljickRKHM3Jdh+O+B0XPoOv6oF7/p2+3WV/vufen4x9LSp0giGYTAfD37DSud5cbo5dI\ni0i2M/LeGUMPZM/cnDtjap2x/QZ2mqYFAgHjIwBomkaFCf0qOozZKLT7KopiyM9yiK7rXKVQ\nZFlmv53Q4Ia9FOPqEAwG2U2iO8yy1924Y0U0g3GkRxDIoOsi1Y7aE7OsXwo9XXde6WVZZr+m\nGFd5XumDwSBXqA08vR0ACCFcXQUY7iUCy4t4RHf0vj5SubQI3t4IAKqqsksft5vwSs/bwhRe\n6XkvRLHPSYQBv/ng0Pb5tT+voSuFkl9m3Qmdev1Pz0EPByUFIOJ1id5H43BGXul5L4+0LF5R\nuMIOqoWqqrzOlVhnpDfBQCAAYD+n35ND++i6rguC8OFLMwE+0HXW616ynTGOCxElDunjcHle\n6bm6PUvOdhrYmc3m/fv3P/bYY/Sjqqqapomi6HK5evfu7XK5jK8iQW/V7LvOAYAsy4QQs9nM\nvoscDUAtFgt7KbRLWSwW9l8M9K5DN2BmtIr6htVqZb+XKIoiiiJ73TVN27cv/AavFFNG7n63\n7dEmuyG7rF1791ZdVvOj5RkAYMrpann6/0U6Sdx155We7jvOmJ92SEEQ2Df8BQBJkngV0XXd\nZDJxVV9VVS6rZFmOrqOjw9mHv6pc+lkx+fXse58JevcGnwn+72eCaHZkHfUK74f3yridMdl1\nbwFnpHWHVDsjAOzfv3/JE/8XoESRbg54f5ClOl2XNFHp3VsW7Z3eXF8A65+MfobW6Yyapqmq\n2gqdkT4HSKwzpuTO2DIXojickQ4ht0VnbKeBHQCcPHlyw4Ywa6Dn5eX5/f6wXyEpIUpcW+PV\ntnib9GGTMy8PggBb6J43P5+E3ahm60W0Out85q99TTZlFiEvDxSAbUcAAKByU0tbhjQhijOG\nu6JaAax5eZmBoIxX1LYC3hnbClGcsZ0GdsOGDeMaBkNSyJgxY8Kmm83mGTNmgK4G928ggQYi\n+4FoBABAEASTYMsSnR1txRe2qK1IZPr27Rs2fdiwYYIgqP7jUt0eNXBCC9brmiQACOYMs73A\nZC+0dzjbhO81tw4iOaPJZJoxY0YLG4PEzYABA8Kml5WVoY5thUjOCAAC+xR7BEEQBEEQpDWD\nS7UhCIIgCIKkCRjYIQiCIAiCpAkY2CEIgiAIgqQJGNghCIIgCIKkCRjYIQiCIAiCpAkY2CEI\ngiAIgqQJ7XQdu/fff7+ioiLVViBMTJgw4ayzzmqaLknS448/3vL2IPExd+7cjh07Nk3/8MMP\nv/3225a3B4mDSM6oquqjjz7a8vYg8XHzzTd37ty5afrHH39cXt5kMx+kVRLJGaHdBnbLly8/\ncuSI1+tNtSFINLKysiwWi9vtXrJkSdNvXS7X22+/jSK2fqiOI0eOHD16dNNvV6xYUVlZiTq2\ncqI7oyRJ6IxtAqrjsGHDxo4d2/TbFStW7NmzB3Vs5UR3Rmi3gR0A+Hy+Q4cOpdoKJBrFxcW5\nuU12mgoBRWwToI5pAIqYHqCOaUBMEXGOHYIgCIIgSJqAgR2CIAiCIEiagIEdgiAIgiBImoCB\nHYIgCIIgSJqAgR2CIAiCIEiagIEdgiAIgiBImoCBHYIgCIIgSJqAgV3SGTJkyHvvvVdbW+v1\ner///vs777zTYrEAQPfu3Qkh3bt3b5S/sLCQENKnT59kGzZz5syvvvrKsKSoqCjZJaYNKdT0\nnnvuqa+vf+GFF+I7Z6vV+ujRo+Q0fr//iy++uOyyy6If0mrrEgdfffUVCcfMmTPD9ijEoKKi\nomm7DRw4MO6+EXe/qqysnDZtWhwlth/CihV9STZGhg0bpqpq88/DK2LrvAphYJdcfvvb327Z\nsmXHjh2DBg3q2LHj/Pnzb7311hdffDHVdv2Ko0ePCoJw5MiRVBvSNkitptdff/0TTzxx8803\nx3d4a9b6j3/8oyAIgiD06NHjnXfeef/99y+//PIo+VtzXXgZMWIErfudd95ZW1srnGbDhg2p\nNq0NsHjxYuHX7Ny5M+6+kU79qhXSVKyGhoZUGxU/rbO3YGCXREwm0/Lly5cvX/6nP/2pqqrK\n7/d/+umnU6dOnT59ev/+/WmeiRMnVlZWBoPBjRs3Nt1J84orrti+fXsgEKiurl65cmVmZiac\n/onwP//zP5WVlT6fb8WKFVdfffX333/v9/s//PDDrKwsAFi3bt0bb7xhnOeTTz5ZtmwZAJxz\nzjnffvutJEkVFRVDhgyh34b+5ghbIgB06tRp9erVXq+3urr62WefNdLbG83XtG/fvh999JHf\n7z906NB9991nMpng9JDebbfd9tNPP91xxx2RslVUVJSVlT300EPLly8PPWdYdRYtWuTz+c44\n4wwAKCsrk2X58ssvb52/LxtRU1PzxBNPvPrqq/QeABEqaNSF/jN16tS9e/cGg8HNmzd36dKF\nnipsMwJASUnJpk2bAoHAwYMHZ8+eHUfmpol9+vQJHV177LHH1qxZQ/+fPn36gQMHfD7fd999\nd9VVV/E2SNgeFbZNGnUklmsFo9kXX3wxr9kpxOgbcTRIqI+wq7x3797i4uJVq1Y99NBDEPmC\n2cyekJbwOk4kPwWAW2+99dChQ9XV1cuXLzfaPNJNram4LCKG7VHR754pIOz4f9ozfvz44uLi\nZLfteeedRwgZNGhQ2G9phygvL+/Xr1+XLl0qKiqeeeYZCHlsZzKZXC7XnDlz7HZ7t27dtm3b\ntnDhQuPAL7/88owzzjj33HM1TTt8+PCZZ57ZuXPnysrKO++8EwBuueWWuro62uOdTqcsy2PG\njMnIyDh+/PiSJUvy8vIuueQSt9vd6FFspBIB4PPPP3/22Wfz8vL69u1bXl7+97//PdmtBwDF\nxcVDhw69++67w4p44sSJFhCxEc3U1GKxVFZWPv300wUFBf369du5c+ef//xnI0N5eXmvXr0A\nIFI2AKioqLjpppvg1493w6pjtVr37Nnz5ptvCoKwdevWt956C1L04IDquGHDhrA6Tpo0qbi4\n+OjRo0Zno1x00UWEkN69e0eqYKPAbtu2bb179+7cufPOnTufe+65KM1osVgOHjz4+OOPZ2Vl\njR07Vpbls88+mzdz08RI96f+/fv/f/bONDCKIu3jT/fcuQ8C4UrCGQhHEEEFAREUFFAEOVTw\nABF08VbUVVkEFZdllUVdd30NKos3itciXiwIAQVFLgk3QQIJhEkmc0+f9X4obMdkjqrJzGRC\n6vcBMjU1XU/1v57up6vr8Hg8/fv3N5vNkyZNEgQhOzs72Lm6//77rVar9jFYiwp2Tuo1JJJr\nBaHZoiiOGDEimDO6XK74OyNm165df/3rX+sl1gvsqE6I9lsqleGPb/ECqkPVEmIEdsYvvvgi\noI5Tp06NqY4BxaJynGB+OmDAAITQt99+27Fjxy5duvzyyy+4LyPYTS2guEAgYsAWFfruGXVC\n3xkRQiywiyHTp09HCOHRVw3BDUJ7Dn7qqaf+97//QaDxWKmpqRdeeOHOnTtxS8U/HDVqFP72\n5MmTjz76KP77nXfe8b/nDRkyBAAmTpxYV1dnMBhuvfXWkydPas83zz//fLAxdvVKHD58eE1N\njfbDkSNHut1u/+ekGJGAgV0jNb3xxhtPnz6t15/boxlLo2W48sorcXqwbBAosAuhzvDhw1VV\nLSkpqaurw51YzSiwKygoQAiNHDkyWAXrBXZXXHEFzvCXv/xlw4YNEPw03njjjTU1NVr6F198\n8cQTT9BmbpgY7P40btw4n89H2FYDBnYNW1Swc1KvIZFcKwjNDu2MTRvY1TNm1qxZ9QI7qhOi\n/ZZKZfCLCYKpQ9USYkSTB3YNxaJynGB+igM7/BwIANddd53P5+P5399J1rupBRQXCEQM2KJC\n3D1jQdjATh+jghkAoCgKAOh0OkmSguU5evQo/sPn8yUlJdX7dvbs2fPmzcvIyNi/f39qaip+\nLVXvh7IsV1ZW4r9VVTWZTABw8uTJXbt2jRkzprS0dOzYsWvXrpUkqU+fPnv27MFWAcDevXsv\nvfRSkhKLi4uzsrLqDU3NzMz0vwO1EBqpaZ8+fX788UftTO7bty89Pb1169aqqgJAeXl56GzV\n1dUNiwuhzsaNG1etWnX77bfPnTu3qqoqsio3FYIgAIAsy/369QtYwXr5Dx06hP/weDwWiwWC\nn8bevXvv2rVLSx8zZgwALF68mDzzs88+2zAx2ESWjRs37tixo6ysrLS09Msvv3znnXdOnTpF\ndSoatqhgouM/tIZU7+cBrxXBqGf2li1bsCIJyJIlS+o9FdSbbhLZCQkoPcl0pWDqNL4lnAc0\nFIvKcYI5NQC4XK5jx47h9J07d5pMpnbt2p08eTLgTS2guP5QuRgmxP06zrAxdjEEN7Ju3br5\nJ6ampkqSpD0yamFWQy666KJXXnnlvvvuy8nJGTZsWGlpqf+3/hdZhFDDn3/++edjxozhOO6q\nq67CD0AGgwEHEJiGXW7BSjQYDIcPH6434rUFRnXQaE3NZrP/lQLHH16vN7JsmNDq4Dtcc5xW\n2b17dwA4cuQIYfPzb9uYYKcxOTm5YVxOlTlgYj3wEQDA5XINGTJk5MiRP/zww4wZM8rKyjp3\n7nz33XfjZ2ufzxf6OBCoRVG5ZNhrBYnZX331Vfv27cOa2iwgPCFUKvsTTJ2ALSHiWpyvhHac\nENdG/ysAfqni8XiC3dTCikt71wt9v44zLLCLIT/99NOJEyfmzJnjn3jLLbc4HI4tW7aE/fmF\nF15YUVHxxRdf4I/4jT45n3/+eXFx8dixY7Ozs9etWwcABw8eLC4u1nqntckTYUs8cOBAQUFB\nVlYW/njXXXft27ePypjzhkZqeujQoX79+mlPcoMGDSovL3c6nZFlw4RQ55Zbbrn44ovnzZv3\n8MMPFxUVEdcyIbj55pt/+OGHU6dORdz8gp3GAwcOFBUVaekbNmyYN28eVeaAifg+oY2Y1k74\nI4888sknn5SWlj7xxBN9+vSpqakZMmTIyy+/jG8VZrM5gpMTRZckNLuurq5fv36RFdFMoVK5\n3g8DqhOwJcSjJokNleOEuDampaXl5+fj9AsvvLCysrK2tjbETa2huP5W0bpYI+/X0YUFdjFE\nUZS5c+fecccdjz76aE5OjsViueGGG5577rl77rnH7XaH/fn+/fvbt29/6aWXpqenP/7444MH\nD05OTvYfNBCan376qaqq6vnnn//qq69cLhcAvPXWWxaLZdGiRZmZmaNHj77pppsIS1y3bt2h\nQ4eWLVvWqlWriy666Mknn1y2bBnt2Tg/aKSm77zzTkpKCpagf//+jz/++AsvvBBxNkwwdbKy\nsv7+978/99xzf//73zdv3vzqq6824asBKlq3bv3YY4/dfPPN+FIbcfMLdhrfeeedpKSkxx57\nLC0t7aabbrr44ovXrFlDm7lhYmVlpd1uv+WWW5KTk6dMmTJs2DBsxhdffHHFFVdce+21SUlJ\nw4YNy8nJ2blzZyNPURRdktDsrKysgwcPNtLs5gWVygDg8/lycnIguDqxaAnnAVSOE/rauHz5\n8pycnO7duz/11FN4mlGwm1pAcYFAxGA08n4dZYINvju/ic/kCcyAAQPWrl1bXV2Nl10dN24c\nTq+3mO1jjz2GpzL4T554+umnbTbbmTNnXnjhhUmTJnk8nunTp9f74fHjx7VZPG+99dabb76p\nFf3aa68hhKZMmaKlDBo0aM+ePYIgbNq06aGHHmo4eSJgiQDQuXPnr7/+2ufzVVRU1HuyiR0J\nOHkC0xhNL7room3btomiePLkyaeeegoHWw1nzATMBkFmxQZUp6Sk5NixY7hDqKioSBRF/0Hl\n8ThNv0E4eUJLcTqdmzZtuuyyy7QjBKxgvckT2ml/+OGH8WmH4Kdx8ODBu3bt8vl8u3fvvvrq\nqyPIHDBx8uTJFRUVbrf7k08+WbJkif+qDQcPHvR4PAcOHJg2bVqIcxVw8kTDFhXsnNRrSITX\nChKzH3zwwYSdPBF2VizVCfH3ESqV//znP/t8PrxSRrALJnlLiBFNPnmioVhA6TgB/XTAgAFW\nq/Wxxx6zWq11dXXLly/XxhoFu6kFFDesiAFbVOi7Z9Rhs2IDE8/ArgkZP3786dOnjUZjUxsS\nIQkb2DGoIAnsmtpGRhgSdlYsg4qmDewYUYHNim2hGAwGnufHjBnzr3/9SxTFpjaHwWAwGAxG\nPGBj7M5PevXq5XA4unXr1mIHwzEYDAaD0QJhPXbnJ7t27Qq9SBWDwWAwGIzzD9Zjx2AwGAwG\ng3GewAI7BoPBYDAYjPMEFtgxGAwGg8FgnCewwI7BYDAYDAbjPKHlTp5ITk5m+/QlONomMyEy\nMBETH6bjeQAT8fyA6XgeEFbEFhrY2Ww2g8GQmZnZ1IYwwlNeXh4w3efzMRGbEUeOHBk5cmTD\n9JqaGqZjcyGYM8qyzERsRhw+fFjba8Efq9XKdGwuBHNGaLGB3ahRo7777rtu3brhj4qiqKrK\ncVxZWVl1dXXr1q379u0b+ggIIXwtIy8Ub3Ws0+nI949DCCmKotdTyIRL0ev15BuDKoqCDSO3\nSpZl2lJkWeZ5nrzuqqoeOXKkrq6uffv2ATNkZWVlZmZqImpW7d+/n1BEaETdaaWnVURV1ViX\nIssyQojnedrq01pVXl5eV1fXrl27gBmuuuqq9evXN4kzxqHu0DKc0WKxBHTGsrKys2fPNmtn\nVFUVG9a0zogAtjnPumUZhTxOV0tqgTklhFXYGbVN1eoxZsyYdevWxdkZ43YhAko3UVUVIdTs\nnBFabGCXlJTUr1+/pUuX4o9Op1MQBKPReNttt23ZsqV3796vvPJK6CMoimKz2Vq1akVeqM1m\nUxQlKSkpKSmJ8CeCIHi93oyMDML8CKGamhoASEtLI99JzO12q6qamppKmF+SJLvdDgBZWVnk\nzdFutxuNRovFQpjf6/U+9thjW7ZsCVYRnuf9RcSKAMAdd9xBKCIAOJ1OnufD9mxrCILgdDoB\ngFb6pKQk8pUF3W631+vV6XTkj85Y+szMTPLLkN1ulyTJZDJRSe9wOLKzswnzA0BNTc2iRYu2\nbNkSrNkHdEaDwTBjxgwqZ8zOzia/mGJntFgsVNJ7PB5aRQAgNTWVSnoqZ5Rlua6uDgBopady\nRp/P9+ijj4ZwRo7j/EVUVbW2thYAZs2atXXr1hg5oyiKDocDAGilp3JGj8fj8XionBEArFYr\nlSIOh0MUxRDOuPrs8X/v3xj6IBxwp3X6DwdNTeID39lra2sXLly4ZcuWYNLXc0aXy4VfjJA7\nI5aeSpG6ujpZlqmcURRFt9tNqwhQOqPH41EUJdbO6HA49Ho9eVQQ1hmBTZ5gMBgMBiPBWWP9\nlYcwoRIC5FSkb21V8TGJkbC00B47BoPBYLRAVEBf1VV97Tx93OfigOtkSRmX1fHKzHak/UtN\nRJmnToXQr2HPsd9Td212x1jbw0hkWGDHYDAYjBbBTlft9MMby3wODjieAwBQa+GlU/svSMl6\ns3Bo3+TEnTTgVmTCnB6VNCfjfIW9imUwGAxGM8YmixWCW0Rq6Gwb605funvtAcEJAAiQgpCC\nEAIEALtdtkG71pbaz8TD3IjIMyfzZKPWOppIR6oxzldYjx2DwWAwmh+nJd+zp/d94qislgUA\n4Dnu0rTWf2rXY2pOp4YRULXkm1j2P0FRA77QVAEJqjJh3/8ODJyYbSAdXB9Prshot6HuNEnO\nkRmBp58zWg6sx47BYDAYzYxPak4U7fzstdrys7KAU1SEtjiqb9z/3cg9X5V56hT0hwBu8Yk9\nNlkMMUxNQcgqC0sq9sbW7kiZkdvNotOFnmrKA4zN6tgp+HInjBZCC+2xQwipqooXtgEAvGYY\nTsQfta+CgXOGzVavUMKDayiKghAiz49+u5YpikL+K1VVqazCS/XgP8jntOM1+ajqHjZPQxG1\nPwhrRKujZhWt9LSK4F/RSi/LsnYeCH8SgfRUdScxI1rOSNUaCQ+ukZjOqDVIWulj6oxa3anO\nM7kzfmmrvP7gRgBUL0xTEQKADXVVvX76RMfxw9Jy5uR2n5CVhwC9deZo2MNyAP85c/SZjsX+\nzSgCZ8RE1xlbcfpnOvZ76PiOYEfggUvW6f+ef0Fj3LPxzogrkmjO6P/DluCMLTSwk2VZlmW8\nBpKGJEn4vtXwq2AQZsPg5isIgiAINMbSlYLxeDxU+RFCEZSCV3QjL0KWZfK6o/oX7cAHbGg2\nbveEIuJSRFEktEqDVnqPxxPBlY5WFJfLRWUV/LY0HdWvImgHTcZ2AAAgAElEQVT2IajnjFqE\nSuuMtK0RAARBIJce/yQyZ6SVPoJSaKVXFIX2QhSaqDgjx3FhFXGp8m2HtwCAGrJlKUj9zlG9\nwX5mRErOX9oU1cjhK4sAzkjegzVn2hnqL/OWCM54a3K7X1vZX7Qe4YGr1/XIAaTw+rfzLsoR\nkUMMegRaZ/RPhBg7oyiKtNfhCNzE6/V6vd5YlxKB9BHcg0LQQgM7g8FgNBq1dVa1BYrxin/+\nXwVDWxOVvFBtTdQ4LFCcmpoahwWKMzMzY7pAcegMHMf5K6UtUIyXIycRERqxQDGt9PFZoDgj\nIyMBFygOnSGgM+JEoHHGrKyslrxAMa30tAsUh83jr5S2QDHeNSe6zvifU/tqFaK74LkOPNfZ\ns2gPSX7MZcc290xKH5+dN6dt93S9MeIFiqkUCbtAMWZ59pBRtQWPHfvpF0+dlqjj+Kk5BYsL\n+ueHewmLRQlBPWfUFigmd0YsPZUz4gWKzWZzHBYoTklJicMCxbTS0y5QHDZPCw3sGAwGg9Ec\n+aymguc4NVznkwYC2Ou2kR/fJgs/OM9udVQvqdi7sseQEWaKx5g4MDarw9isDgc89h2Os2dd\nzq5ZrS5Na5OpJ32MZ7QEWGDHYDAYjGbDYY+DPKrDnOs74riw7yIx+Ph1snjtL/97q8ugUaYs\nWiNjTY+k9K7GZLvBnp2VWHEnIxFgs2IZDAaDEWUQwK+Sp04RAQCRbZlAiEwZ1WFjEMEIs3qo\ngDiAO8q3n5bDv/xiMBIH1mPHYDAYjKjhUKSlJ/aWVB06LfvAXg0A/605Ofvw1vl5xVFZO7ez\nJfWs7KPttAOAdJ3BqcpUP1QBeVX5ReuRJe2LaYtjRAuvqr5z5uwXtbZyn6DnINdoSOd1JkVR\nz1jzzKYrMjMuTU9L8B3h4gwL7BgMBoMRHfa6bWN/+bZCcPuPnZcRKqk69M6ZY+/2vOyaRm9j\nOiar/feO6gh+ODO3+5tnDttliXDTVY1PHVUssIsbCOBHh+sbW12lKJp5DiF458zZM5LEc/Xn\nQXMcIAQLj1dckJryavcuA1PZAn7nYIEdg8FgMKLACcE9cs9XNZIADd57IgCvqkws27C+7+hh\n6W0aU8qctoV/PbHXqyq08dmQ9NZ3t+9xe9mmja6zANBw0ZCAIIBqWahTpMTdR/Y84ien60+H\nj/7ocAEAB7/Jg3f1baCV1sR2u9xDdu79oKhwfKuEGw3ZJLDAjsFgMBhR4N4j22pkIVi0hNPH\n/fKtgefrJBHft3MM5uty8ua27dEnmTRwyjGYX+52yYyDpbjDhhxBVTubU9d0GnwICetd1Zvt\nZ760nSL8rVcNvyoso5F8Zq2dXHZQ/m3P39+1DaeyipCM0I1lh34eUNwjiXQRn/MYFtgxGAwG\no7G4FOnTmhOh86gIORUJcIyEAADOSN5XKw/+X+XBa7I7vtS+XzZvJinrtjZd7bL44LEfOQ6F\nXqZYgwNu9uEtG+1Vm22nq2Vfut7U1UK6PpkeuFZsPZEYc9An3FB2iGLHhj+iAvhU5dFjxz/t\n3TPKljVDWGDHYDAYjMZyRox86igC+KymYm1Nxb25hc90HZjEn7sxHfY69rptdllsa0wqTs50\nqnIyr29jNOs5/r72RZckZS04vnO9s1omeqOKXIr8f1WH8Au+Glk8LhBtD8Bz3KCkLAPHVpCI\nLU9WVAqqEllUh0EA/62xWSWplcEQNbOaJ/EO7GbPnj116tSRI0dGfARFUVauXLlhwwZBEIqK\niu68887c3NwQ6QwGg8GINW5VbuQRFIBlpw/+z1X9TZ/RP7tq/ly+Y6crwE4J6TrDhFb5j+f1\nvSA5662OA12q/AN4bzzwHWEpWgxIOD1WRWhmZgHhwRmRYZWVL+32xi+KoyL0g8M5Lrulj7SL\n01OIoigVFRWvvvrq6dOnG3moFStWfP/9988+++ybb77ZunXr+fPn4x0Pg6UzGAwGI9ZEa72J\nPa66AT9/fvXeb3YH2S7Crkgrzxzp9dMnK84cAYAUXq8n3r0qAq5Kbzc2rW3sjs8AgB89Xvrl\nawJTLUrROVBzJk6B3cqVK+fOnbt27dpGHsfhcKxbt2769Ol5eXlJSUkzZsywWq3bt28Plh4V\n4xkMBoMRmmRddN7/IEAnBDcK2aOGABSE/lS+/f26kwAgxGBmAwccAAxLz32zyyVsjbRYY1Wi\npmB2i38PC3F7FTtz5syZM2f6fL4pU6b4p4uiuGrVqk2bNrnd7oKCgkmTJl1yySUhjrNv3z5F\nUYqLzy0pZLFYOnXqtGPHDr1eHzB96NChMaoRg8FgMDRyDRYu/PzFqKEC4oGbd3rv5Sk5eebG\nrnvMccADp/iFkhl6w6Md+zzYoZfk9XlAbOTxGaHJ0OmichwO4EK2ml2TT55YunSpx+N57rnn\n0tPTS0tLlyxZMn/+/P79++NvbTbbrbfe+tJLL+Xn5+OUqqoqo9GYkZGhHSEzM9NmswVL1z7W\n1dW98sor2sfa2lpFUVyuc4NnZVnG/2p/aF8FA6/SFDabP3i6jyiK5PN+FEVRVZWqFIzP5xNF\n0ouRLMsIIfJSNPvd7j8sQxoaRVEEQVCIn8ywFiFACPkrpa2bhYsgERFn4ziOvO6a/bTS+3w+\nSSJ9R4BzRiC9x+OhUgSITxRGVVWqpgIE+zgpiuJvA9YdJxKah4twu93kVmnOSL7NFK0zakem\nkp7WGbVSaKWnckaSnEYEk7LyPqytiO4GYiFQAXlV5bXa8vkd+6boDG5FirhghKDQnPZ0+z7H\nRbeB47uYUgalZBs4XnB7cDtsmc6I220cnLGv2USePxg8B5empGRIoksKeu+LqTNqd0Yq6WVZ\nVlWVKioIm6cpA7sjR45s27atpKSkdevWADB69Oht27atX79eC+wa4vV6jcY/TDu3WCzV1dXB\n0rWPHo9nzZo12sfi4uKUlBSf7w/TuLSTi2/DJFUgzOaPFj6SE0Ep5FGdBvlVXoN2FKOqqrR1\nD3vAhieHVkQgCCIbQiuKJEnkFxQMQoi2lAjGlSqKQit9BA0yBNjvmsQZ41P3CKRvps64KKfH\nFkd1leyLW78dAPepo+oJoceszIJ/WA835kBORRpmyhhmOtc7oAiivwbMGSGWzphvNFxoMe/0\n+QgXr2kIB8AhmN86O3TRLcQZmzKwO3jwIADMmjXLP7GoqCjET5KTk+udMkmSUlNTg6VrHw0G\nQ8+evy9vY7FYOI7T689VHzdcjuNwlO3/VTAQQoqihM3mj6IoCCGe53medGgjQkhVVR1NNzVu\nHzqdjvyJAT/5kZeC6w4AtNXnOI687iRPMP5KaVaRixiBVRHXned5KkVw9alKkWWZSnfcIDmO\no5We1qrQGbDf4WMe9Fn/U7Nzk/PXKtnpc5UDQJXs4nU6PmSlIrYqps6oNRWqUmidESJy+Qia\nfdg8HMflmpJuzi5YcuZgHF/JouOS5wySHsotXOs8fVRw0W5HgeEAOhgtAZuQdnegFaW5OyPQ\n3xlFFf3k8R73eU16fVejsW+ShaT+uO5PtW1zbfmvHHAR9PjyAAhgaYe2IXYVa1F3xqYM7HB9\nVq9eXa+z7Ycffli8eLH28Z577sF/3HXXXdnZ2ZIkOZ1OLWizWq2FhYXB0rWD5OTkrFq1Svv4\nwgsvVFVVaa9unU6nIAgGg8FgMACAwWDwf6sbzHibzRY2mz82m01RFLPZnJSURPgTQRC8Xi95\nKQihmpoaAEhOTq53VkPgdrtVVfWPg0MjSZLdbgeAtLQ08uZot9uNRqPFQrosuNfrDZ2B4zh/\npbAi8JtTkYgIAE6nk+f55GTSMTqCIDidTgCglT4pKclkIn3d4Ha7vV6vTqejlT4tLY38MmS3\n2yVJMhqNVNI7HA6quuMGGQK9Xm8wGFLT0x499sWyk5sRqIAv7aoEAD97KkccefPD3jd3tbQK\ndgQsfXp6OvklGzujyWSikt7j8UTmjFTSUzmjLMt1dXUAQCs9lTOSdMAYDIafkOdv1QcIjxkt\nEEJPWQ+u7jn86+LRV//yzQGPPYKhfghgVKuOAcX1eDwej4fneapmb7VaqRRxOByiKFI5oyzL\ndrudyqra2gDLx/iDnVE7psvl8vl8OBFCXlRdirLkxKnlJyudfv1b7YyG+QV5s9vm8iH9sq6u\nTpbly7Mzl3Lcw0eP8wAkbyU5PL0FOBWhNkbDv7p3Db2fmNVqBQCq67DH41EUJQJnTE1NpZJe\nr9eTRwUkztiUgV1+fj5C6NChQ7179wYAhNBdd901dOjQadOmffbZZxBojJ3T6dTr9Xv37h08\neDAAuFyu8vLyG2+8sbCwMGB601WOwWBQMH3/u+9V7wr41V7P6Yt3vLTtwntCxHaMJgcB3HN0\nW5MU/dHZ4xWd3QXmlB8vGPe3il9eqtxfJ9ONReE5mNGma4zMO+85KYhX79n3i9tTL347Lcl3\nHTr63xrbB0WFSbrwXQAPdWzf1mi89/CxGlnmgUOA8K5xCGBwetq12Vk2WdZxAAA1glju8Yi8\nLt9suiIzY2KrbJLjtxyaMrDr27dvYWFhSUnJww8/nJaW9uGHHzqdzjFjxoT4SWpq6ogRI1at\nWlVQUGAymV555ZW8vLz+/fvzPB8wPW51YTAYEVPuq/0oSFQHACpS6xTf5LJVO/rfH/qdLKMJ\nqZGEAx57kxSNAL62Vd6e283E64w8L9HvSjUlp1O+mc2mjASvqo7dW1bm9kKDjlK8YM3amtrb\nDx5+t6gw0K/rc1ObnHHZWe+fta631VUIQjKv65lsub5Vq2EZaf7ZRFF0u92ZmaT7C7c0mjKw\n4zhuwYIFr7/++rx58xRFKSwsXLx4cVipZs+e/cYbb8ybN0+W5X79+i1YsAC/DQyWzmAwEhkV\n0H53Nc9lh1i3TEXqLmflGuveSTl942kbgxyrFM1R/LQc9DrW2U7OO/rTPk8dbexv5vUrug+J\niVktgOUnK/e4wsyBfa/aeltum9FZRG+N0/S6O9q2uaNtm2hY10KJa2BnNpvxO1aNlJSUe++9\n99577w2YPzMzs15+ADAajXPmzJkzZw5hOoPBSGQqfHUCksPu78Rz3AfVu1lgl7C4lKZc8f+F\nk78srdiL/6YdYDcqs20SH5111FoaCOClk5X4hWkIeA5eOlVJGNgxGg/r02IwGE1JjewhyaYi\ntMddFWtjGBHjaNLATmnEjlTf2c/Uymz/yUjY7/FWilLYc68i+NZmj3gpEwYtLLBjMBhNiUi8\nebyT3X0TGAlRj2xLEOyy+OTxnU1tRfMDAdx/5BhhZkFVz1IuIMeIGBbYMRiMpiRFR7T6AMdx\nHczsVU7i0nwDOwAoqTpko5xIy3j5VNU3tXXk+dnE1bjBTjSDwWhK8kxE4RpCMDKDLUiRuIQd\nJZnISEj91lbZ1FYkLi5FAYB9bs/C4xUfVFvtsuJWlAXlvxLOU+EA2hmNqVHaEJYRlibeK5bB\nYLRw0vTmNobUco4LHRkYeO72thfFzSoGPc17JZpyH/WW3C2Bw4L4+K+nNtrqAOCQ1/vU8RMA\nYNbx47KybDLxXlscTG7NFqGMHyywYzAYTUyflNzdnMELshr8dd6f80Z2sWTH0yoGFRHsBJVQ\n6NgSiX9EQujxispXqq1KA2UFRf3wrJXwOByAmdc90rF9tA1kBIW9imUwGE1Mqs60pvetFk7P\nN+j1wZ9nth24IP/K+BvGIKc5v4kFAOhqId05qiVwzOvrtf3nl86cVVCAiJ1KagTwZmHXdibS\nLS4ZjYcFdgwGo+kZldV9x4D7r8ruwf0xtjPzhpU9blhROIXtOZHI1MpC843rcJfSyIy2TW1I\nolApiEN27jnijc4k9AGpKVPYe9j4wl7FMhiMhKAwKWdtn5kHak5tsB2xIu+alB93weHRWYW3\n5F7Y1KYxwrDDGWZ3+UQGAdzfvihFZ2hqQxKFOw4dOS1J0YrUJ+WwERTxpoUGdrIsS5JUV3du\nqraqqgAgSZIkSfgP7avQEGbzL8Xn84ki6bx6hJCqqlSlYNxut8dDtO4rNgwhRF4K+u2li8Ph\nIDdJURRFUQSB9ClQDbfhI0LIXynNKlmWgVhERVFwZkKrtFJopXe73V6vlzw/to1WeofDwRH3\nbOG6i6JIJT1VUwG/MxaMes6YA+bJGb04jtuuS90FIBPoiIuw2yk2KsV1FwSBXPqI3YRWetoz\njKGVnsoZw4r4sfU44aESDQ643pa0ezMKgp1z7IwRXIedTid55gicEQBom0rYi6osy1af74sa\nG/kxQ2PkuLFmU2gjI3DGiO+MHo+H9jocgcvTSi/LMnlUEFZEaLGBHc/zPM+bzWb80efzqaqq\n0+nw9rL+XwVDVVVZlsNm88fj8SCE9Hq90Ug62gDf88hLQQjhsMZoNOqI55YLgoAQIi9FURTs\nGyaTifxe4vV6dToded3DOjnHcf5KqaqKY1lyEQHA5/NxHGcyES2lBgCyLOPLEK30RqNRryd1\nN0EQVFUlrAIGS28ymci3SPZ6vYqi6HQ6Kul9Ph9V3V2uMJMNGzqjLMs4EYid0ePxULVGj8eD\nXZ5KelEUqRRxu90AQCs9lTPiCxEA0Eqv1+sNBtI+qrDOuMsTtVAgivDAdTIl55mSU/WGr2xV\nIlIAOG3IGM9xKkKDUlu9121Ipj5oMxBFURRFjuNom73RaCRXBDd7KmdUVVVRFCqrcIMMAc/z\n1QrxXFcCHmqX2zUtzOBFfGekckb8WBLBhchgMJA7oyiKqqpSKYLvQbTS8zwfxTsjtOTAzt+F\nJEnC9xIcDJF4l6IoHo+HqmHhYEiv15P/ShAEqvBRu5cYDAbyhqIoClXzlSRJC+zIm68gCAaD\ngaouYfP4K4UVgd8CO8JLpCRJVPGTIAg+nw8oAzuv12swGKguW5IkUd1LsPQmk4kqoKcN7CRJ\nog3sSO4l0XJGqscMoHdG2qcszRmppKdyRlmWcbOnlZ6q7mGp9Hks0TpWo+GAQ4AKk9I+7TWy\n0JKOEytFz18r9r5fXV4t+QCAB25ASqu72hXe0qZLwyk7/qiqGllgR6UI7rChckZZlr1eL+0T\nZugMPM+7VaTjQKF5Ecs3WKsISzA5p9XTXTuFnW6MO1aoGiSOtiML7MidkTZ0jswZRVGMrjNC\niw3sGAwGgxEtXIqUMIEdNzC11YzcrrfndjNwvz92tjMmvdjl4he7XHzo7GlkMnZMSUvi2e0v\nACpCgDjCma8cB0WWpDpZPiWK4Bfhpei4vxTkP9SxPZvx1CSQtuyjR49+9dVX69evP378+Nmz\nZ/V6fatWrdq3bz98+PDRo0f36NEjplYyGAwGI2GRE2axk6WdL3y4Q+8QGXL0piRTkolFdUFI\n0ulU4vVMEILhmWnPd+n0rc1eandUS1K6ju/BwZS8vAwDO8NNRvhT/9133y1YsOC7774DAJ1O\nl5GRkZWVxfP8r7/+unv37k8++QQABg0atGjRoiuuuCLm9jIYDAYjwZAJBnTHFB44FdAdbbs/\nFDKqY4SltcFAFaSfFCQTz4/NzhybnQkAqqrW1tam69nuYU1JqAFSVVVVN9100+WXX44Qev75\n57dt2+bz+axW66FDhw4cOHDmzBmPx7Nr165///vfycnJo0aNuuaaa44dOxY30xkMBoORCKhc\nE/fYZemN/9dt8P91G8ze/TUSA+WCkVtoZqMz4kOoHrvevXuPGzdu7969vXr1CphBp9MVFxcX\nFxfPmTPnwIEDS5cuveCCC6gWHWAwGAxGc4eL70axPHAGnru9TVdRkDJ1hiE5Ha7Mam/hWS9R\nFDgp0q1LXCvLKgKeBdSJRKjAbvv27V26dCE8UI8ePVasWPGXv/wlGlYxGAwGo/kQg/u6nuNl\npHIcV2+CPM9xBo57v+fwq1Nz8VKa2dnZ5BOiGaE5KZAuqIZJ0+lYVJdohHoVSx7VaeTn5zfC\nGAaDwWA0P6I+d4IH7tu+o57K79ewH+6i1FZb+40dn50X5SIZAOU+n0AzXJLj4KJwy9Qx4k8k\n81YkSXryySdLSko4jps1a9YzzzxDvuIfg8FgMM47ohnZGXndmqLLL0vPvSw99/72Retsp/Z7\n6uyy1NGUPCKj7QUpWVEsi+FPmZt0vyIMQjCtdU6MjGFETCQB2bPPPvvRRx+98MILHMctXLgw\nOTl5/vz5UbeMwWAwGM2DqHbZTc/pPDqzHf47XW+8IadTFA/OCEEl8cZWmPZG07Q2LLBLOCIJ\n7F5//fW1a9f26dMHAIqLi8ePHx9ZYDd79uypU6eOHDmS6leKoqxcuXLDhg2CIBQVFd155525\nubkA4PP5Vq5cuWXLFq/X2759++uvv37o0KERWMVgMBgMKtSojrJ6/cxhA8//u9ugaB6UQUCt\npFDNQFnYqUPYjSUY8SfMflClpaUNEx0OR7t25x6nOnToQDsNVlGUioqKV1999fTp01Q/xKxY\nseL7779/9tln33zzzdatW8+fPx9vZf2vf/1r9+7dzzzzzH/+859hw4YtXbp0+/btERyfwWAw\nGFREfYzdq1UH19aejPJBGeFQaF6pm3juBvYeNiEJE9g98sgjU6ZMKS8v90+8/PLLH3zwQZfL\n5XK57rvvvhEjRlAVuXLlyrlz565du5baWACHw7Fu3brp06fn5eUlJSXNmDHDarVu377d5XJt\n2rRp2rRpeXl5Fotl4sSJnTp1+uqrryIogsFgMBhNC8/B0yd2N7UVLQ6VJkC/v0P7ZOIdURnx\nJMyr2K1bt7777rtXXXXVhAkTHn/88bS0NAD4xz/+MXr06IyMDIRQ9+7dv/76a6oiZ86cOXPm\nTJ/PN2XKFP90URRXrVq1adMmt9tdUFAwadKkSy65pN5v9+3bpyhKcXEx/mixWDp16rRjx442\nbdooiuI/jTcjI0OSJO2joij+HYSSJCGEFEXBH/F0eoSQ9of2VTBwhrDZGkJycA1VVanya+sC\n4N2LY1SK+tu0KUVREPGjOkKI1iqSY2oHbKgmSVkRW0UlPW0pVFXw/wmtVbSl4OpH0OzDWhIV\nZyRf8yKyuie4MxL+BGLjjNFFRbDdcfaU15VrDLoJrX/dqaSPwBmBvtk3R2ckj+tMHPd4h7YN\nS9esSihn9P9hHJyRyl9i4Yzhx9jdeOONEyZMeP755/v37//II4/cfvvt+fn5O3fu3Lx5MwAM\nHTrUYonO7s9Lly71eDzPPfdcenp6aWnpkiVL5s+f379/f/88VVVVRqMxIyNDS8nMzLTZbN27\nd//ss8+0xJqamv3798+aNUtLOXPmzPjx47WPxcXFKSkpNpvN/+CSJOFYUJKkel8FgzCbP16v\n1+v1Uv0kglJcLhftT0TKYbMAQPsWXpZl2rqHACEUUClZloFGRADAb/OpoBXF7Xa73W6qn6iq\nSlsKXtaLClEUaaWPoEGGAPtdvWPKskzrjHV1dbRF+3w+n89H9ZMI6h6B9BE4I6300XXGWIAA\ndp2tvDgp/BxYWukjUERRlJbgjOShnR440eEIZmsLd0baO6MkSbR1D02YV7EYs9n8xBNPlJaW\nbtu27cILL/z2228tFsuoUaNGjRoVrajuyJEj27Ztu++++9q1a5ecnDx69OgLLrhg/fr19bJ5\nvV6j0eifYrFY6l2ejh8//uSTT44cOXLUqFFRsY3RLPCovp/cBzY4frYrdH7LYDASExE18Ra0\njGAIUR9WyYgeFLNic3NzV6xYsWvXrgceeGD58uV///vfCwsLo2XHwYMHAcC/jw0AioqK1q9f\nv3z5cvxx3rx5ycnJ9TpXJElKTU3V/n7vvfc+//zzGTNmXH311f7ZWrVqtWrVKu3jmjVrbDab\n1vPn8XhEUTQYDAaDAQAMBoN/p2BAVFV1OBxhs/njcDhUVTWbzWazmfAnoigKgqBVMCwIIfys\nkJycjOtCgtfrRQglJSUR5pdlGfcIpqWl8TzRswEAuFwug8FgMpkI84ftReM4Dit1yFOx8PiK\nT6o3iUgCAHAeAoAy4VchSW1jDPO47/F4OI4jfz4RRdHj8QAArfRms7neM0kIvF6vIAg8z+PB\nDyRg6WkVkWXZaDRSSe92u9PT0wnzA8HDq16v9/c47Iw4EWicMT09nfztD3ZGk8lEJb3P56NV\nBACSkpKopKdyRkVRnE4nxNgZI+i0iAp9WrXNMCUH+1aSJNz7Qis9lTPiniQqZwSAuro6KkXc\nbrckSVTOqCiKy+WicsYIOhGDoeO5gI4ZgTM6nU5FUaicUZIkr9dLqwhQOqPP51NVNdbO6Ha7\ndTodVVQQNk+YwE6W5QULFpSUlADA7bffvmjRon79+m3YsOGTTz6ZMGHClVdeuWDBgqysKCwX\niV/Jr169uuFJ918PZfPmzZIkOZ1OLdaxWq04vrTZbM8884zdbl+8eHHXrl3rHcRoNPbs2VP7\naLFY6urqtHWVcRPkOE77I+ySy/iNONXKzPjgPM+T/wqfFvL82nAQnU5H/iue51VVjaAUvV5P\n3nw5jqOqu/8QyRDHXFPz3S2/LBKRVG+0X7m3st/2Wz7tt3RwRp8oWqWNhKCVnlYRIGuHGrj6\nOp1ORzycmby11ysluguSY7+LijOS30vOG2fUoJWequ54eEM84YHrYkntmhwqatEGG9FKH2tn\nxMTaGTHRdUaeeG84fRBTsSixdkZVVSM4V0DvjAih5uiMYe7Kzz333Ntvv71o0aKnn3767bff\nfu6553D6ddddt3v37vz8/IEDB2o9ao0hPz8fIXTo0CH8ESF05513vv322/Wy9evXT6/X7927\nF390uVzl5eV4HN7SpUtFUXz++ecbRnWM85Vq0XbT3r9ISA44h6NWdl798/0H3SfibxiD0bKI\n9lpmKqCHO/SO8kEZ4dATR2OkD/SMpiCMOiUlJR9//PGcOXNmz569Zs2aFStWaF8ZDIYHH3xw\n+/bthw8fbrwdffv2LSwsLCkpOXnypMPheOONN5xO55gxY+plS01NHTFixKpVqyorK2tqapYt\nW5aXl9e/f/9Dhw798ssvDz30EFW/NKNZI6jSTudBhMJA3LAAACAASURBVEANMhBHRapL8d51\n4G9xNozBaHFEdcAVBzAys93tud2ieVAGAeThWhpb6CSBCdP7Z7fbCwoK8N+dO3duONUlOzv7\n5ZdfbrwdHMctWLDg9ddfnzdvnqIohYWFixcvzszMbJhz9uzZb7zxxrx582RZ7tev34IFC3ie\nLysrA4B7773XP2fv3r0XL17ceNsYicnnZ0s9iqBCqOuLCmhD7Y5dzsP9UtlNgsFIdHgAFeDy\njNzVPYezLQ3ijwyIcGh2GtsgPoEJo83w4cMfeeSRl156CQAefvjh4cOHR6tgs9nsv0AJAKSk\npNx77731grOGGI3GOXPmzJkzxz/xuuuuu+6666JlG6NZ8E3NNsIL/5c137PAjsFIfPJMKY/m\n9ZmV203PsXd9TYCMgDCwa2sinZzHiD9hArt//OMfV155JX6/mZeX980338TFKgYjPCeFsyTZ\nOI477q2KtTEMBiMyOIAOpuSS7pe2VrhulrTk5KDTYBmJQ98U0rmijPgTJrArKCjYvXv3xo0b\nAeCyyy5jLsdIHEif6REycOytAYORoCCA6a27jMpsh5eKYDQppIMlc/Ssxy5xCXVrXL16NV5R\nacyYMWPGjAkb1amq+v7770fVPAYjKF0sHUguQgige3JezK1hMBj0cAAmnv9Tu6gticqID5vt\nLApPXEIFdk888URRUVFJSUnYnWe8Xm9JSUlRUZG2HgqDEWvG5lxKko3j+HGtiHIyGIz4wiGA\nFzpf1CH4KsSMeMIRr1vzta3uuI96J0ZGfAj1imrv3r3PP//8Aw88MG/evDFjxgwePLh///45\nOTmZmZkIodra2rNnz/70009btmz5+uuvFUVZuHDhfffdFzfTGS2cEVkXZhhSOPChkK8Pbs4d\n3cnSLm5WMRgMQjiAZzv1/1O7Hk1tCOMc5KvWqAh9dNb6UMf2MbSGESmhAjuTyfT444/PmjVr\n6dKlb7755jvvvBMwW25u7p133nn//ffn5ubGxsgYIqvijtMf/1z5+VnPcaPOfMJR3tQWMUjh\ngEvTJSMI0518QRp7y8NgJByZBuO63ldenJrT1IYw/CEN7TiAPW5PTE1hREz4QeWtW7deunTp\nkiVLfv75540bN546dcpqtQqCkJmZ2aNHj0GDBl100UXk+0olFGXW9St23271/soBDxwC4M56\nVAA4ULOxynWwbQoLCBKacm9lha869HACDrhnjr0xu/34JB3pTnwMBiPW6Dju6MBJmXrSXTsZ\n8YL0VSwCcMhKTE1hRAzFpmkDBgwYMGBATK2JJzbfqaXbRuMHFATquf8BAMAt1S0svejPgzbm\np1/QlCYyQvJh9YbQL2EBAAGqkexf1vwwsfXwuBjFYDDC83CHXiyqS0gothAxN88OnZZAC10G\nwiXWltf91BEhBAF3o0I+xfWPH69dOHi3SRd4VC/e6lgQKEaP4v1MFUUh/5Usywgh8vzalqmS\nJAXcPjUgiqKoqkpeCt5zHQBEUSTf6VlVVVmWqeoeOsMO+wHCsrfW7hmbPiiYVVRnWJIk/Aet\n9NoPScBnOALpRVEk7z7HbZiqQWLDqOpOYoZ/88NF4ET8R9jiNGckb40ROCP2qcickfAn2CSq\nUnDdgV766DojLRMyOjQsnbbumlW00lNVJwJnxETgjFTX4YjvQdGio0HXsHRcRKydkfbO6P9D\n8syNuTM2rTO20MDupGMvAjVIVAcAgJBa6zv59bEXR7YPNR3E46EYZICbryRJ5G0LIYQQoioF\nIwiCKIqEmfEFgrwU7eoQdrp0vVJEUaSqe+gMNZKd7CrFnfHWBKudFtzQWkUlCq47+Q1eu8rT\nSu/1esmvp7jWiqJQSU/bIMPqqKqqZsMxofZbx9HjQp2B58u9NYTm4SJoWyMASJJEJT2VIlrF\nI5A+ApenlZ4qvoluQAAAWXKAOuKWEIEz0kpPdXnEpUTgjD6fj8oqAJBlmda5ouuM5K9iAWCA\n0Ris9AicUZZlKunjcGekLUU7vbTSR9bsQ9BCAztRDd/sOI7/2frhpN5PBfxWURSbzRZwN9tg\n2Gw2RVHMZnNSEuma3YIgeL3ejIwMwvwIoZqaGgBISUkxGknfdLjdblVVU1NTCfNLkmS32wEg\nPT2d/LnEbrcbjUaLxUKYP+ylwacS3iyR0WQKppTT6eR5nnzlbUEQ8DKqtNInJSWZTCbC/G63\n2+v16nQ68lKw9Onp6TrizbntdrskSUajkUp6h8NBVXfcIEOg1+sNBoPDAvcd+fRT677fv/Ce\nAYC9QjWkmjP1oZoNdsaMjAzyyEZzRirpPR4PrSIAkJycTCU9lTPKsoy38KaVnsoZqW5UJOzj\npesy60+2o3VGURQdDgcA0EpP5Ywej8fj8VA5IwBYrda0tDRyRRwOhyiKVM4oy7Ldbqeyqra2\nljxzWAblts5scBpVVa2traVSpK6uTpZlk8lEJb3b7aZVBCid0ePxKIoSgTPSSq/X68mjAhJn\nbKHvyAXFHTYPQmqlq0xSo3xFY0SLWslOmPOMGCa2YDQtdbL3wh3LP7eWNfzqV59t4E/LK4S6\n+FvFiB3vVB9tahMYASDvrzNwfEfiCIkRZ1poYKcioncQCJBbssXaGEZk2CTSpc/ZXrGJjE+V\nvnf8apM9apCB2+W+2vG/vCmjoAMnGM2OX32upjaBEYCw09E0TKQdUowmgCKwQwitXbv2wQcf\nvPnmm3HK+++/H/WxF/FBR7Z5KM/xqcZWsTaGERkiIh23ZCXu22PEn12uSp8qq8GvJCqgnc5T\nK6q2x9MqRoyhGMvFiCOkuphaaq9Qs4BUG1EUr7322nHjxi1btuytt97CiTfccMP1119PNecr\nQTDrw7815zi+U8ZFOo5tdZygkO9+w7O7SALjVMJPB+M5vqRqWxyMYcSHTma2h1jzJt/CVgZN\nXEgDuxdffLG0tPTll18+duyYlrhixYqNGzcuW7YsNrbFEJLADiF1WMeZcTCGERmpOtKh33nm\nNjG1hNEYHHL4YawqUnc4T3lJp8swEp1prbs2tQmMAHDEr2IvJZ5SwIg/pIHdypUr33jjjblz\n53bq1ElLnDlz5j//+U+tA68Z0TGtr543clzQYQIc8PlpFwztOCOeVjGo6JbckTDnsAy20HTi\nIiKief4IULXIBmadJ3S1sLAgMSF9uTE9l+0Fl7iQBnaHDx8ePXp0w/Srr7766NHmN7/JpEvu\nknGJiU/iucBnINuSd//ATwmH4jGahHSCbldMhiElppYwGoMuiA82JPSiJ4xmhIF4LQxGPNET\n69KLeGkSRvwhvaSmpqZWVFQ0THe5XHp9s4x+UozZTw3d3j1r2G8JnDZmK8vcceHQn7IspB1C\njCbhuK+SMOfPjoMxtYTRGHwK0QvWXGNamp4N6zkf4DjoaGJhQSJCHnA7lShvRsKIIqQx2ejR\nox966KHVq1ebzb9fWz0ezwMPPDB06NDY2BZz2qb0+POgDb/ad/508tNqd7lRbz6S9sMJ2NMp\nY0CKMbuprWOE4axYR9hld8zHljtJXFwq0ULwIhtgd76QwhtNPFstIxFJ1nGEwx1cClt+KHEh\nDewWLVo0cODAoqKisWPHAsDChQuPHDny+eefC4KwdevWyMqePXv21KlTR44cSfUrRVFWrly5\nYcMGQRCKioruvPPO3Nw/rGB+6tSpBx54YM6cOYRHzk+/IIvvKgiC0Whcm3QbwB4qexhNhUq8\nsBn54kyMhMUme2VV1bN9x5s/PZLZ0IgEpZXeQBLY8Ry0NbL1IhIX0qtk586dS0tL27Vr9/LL\nLwPAU0899dZbb+Xk5Kxbt+6CC+hGpiuKUlFR8eqrr54+fZraXoAVK1Z8//33zz777Jtvvtm6\ndev58+f7756rKMrzzz8f9Q1wGAmIgSe9sqTwbGxW4iKqhJMnYL/nTKyNYcSBC5LY4qAJSroh\nfF8PB3BRamoy8ZZZjPhDMTyuZ8+epaWlx44dKysrk2W5oKCgb9++5FuFaqxcufKTTz6h/RXG\n4XCsW7fu/vvvz8vLA4AZM2Z8880327dv114Hv/322zqdLgKrGM2OZJ2ZsCMuXc96CBIXBamE\n7rrV8WuflLaxtYYRewS2iUii4iF4wYoALk5jk5oTGooA6J///GdxcXHnzp3HjRt33XXXTZgw\nYe7cuSdOnKAtcubMmZ999tkHH3xQL10UxRUrVtx6662TJk16+OGHf/jhh4a/3bdvn6IoxcXF\n+KPFYunUqdOOHTu0b7/44ouHHnqI1iRGc8QApI+MKWzQfQJDfpN3KKwn/nwgjbivnRFnknTh\nQwIOYJcz/GbrjCaEtMeupKTk7rvv7t+/v5bStm3bkpKSDz/8cMeOHbj/rJEsXbrU4/E899xz\n6enppaWlS5YsmT9/vn+JAFBVVWU0GjMyMrSUzMxMm80GAB6PZ9myZXfccUe9IXeY2trav/3t\nb9pH/PbW6Ty32agsy/hf7Q/tq2DgvdTCZvNHVVUAEEVRUYjePeGfqKpKVQrG6/X6v6EODa41\neSm4IgDgdlO4t6IogiDgsgjzhzGDuGi74A5WO2yPViNyq2il9/l8okg0S8DfKlrp3W43Rzyv\nDddFkiRa6amsiuKug7VeV8CicREuF8Uqd5ozkktP64xaxb1eL630EZRCK310nZGKIUmZAStI\n64xaTlrpqZwR1z3Wzkh+69GI4B4U1hkdUvgmgQBKHY5qu90S6M1YBM6Iz3BMnVGDVnqEUKyd\nUZZlVVXJXYwkJ2lg9+9//3vRokXz58/XUrZu3Xrs2LFp06Y9/vjjjV+j+MiRI9u2bSspKWnd\nujUAjB49etu2bevXr68X2Hm9XqPR6J9isViqq6sB4F//+le3b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Z2c4zh/pbAi8NvobBIRAcDn83EcR77JjCRJ+HZIK73RaMR7/pKAr3E8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\n9KVLlwKAXC7nMUAikZSUlDAMExwcHBgYGB0dfffu3dLS0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6EMTaC+kjMefEZSKkSsGTKZLCEhYd26dezP8PDw8+fPnzhxIjw8PCUlxcbG\npl+/fuwhPz8/ou1uyMvr6WssTExM5HJ5cnKys7Ozq6urOn3AgAHqm4/Bgwer04cMGXL+/HkA\nqKioqK+vT0tLk8lkv/32GwCwxa3VGLanU0/bsIwYMYL9wk6fNqPVvPivEeFHYmBGgZZJ9CeS\nYjNdlVtaWgLA48dalro8PDye5iKR1NU9s+eJp9LVJ4rFYpqmnZyc2J8ikaihoQEATE1Nx40b\nd+TIkVWrVmVkZDx48CAyMhIAUlNTnZycnJ2d1Xa6ubk1s6rVfPmdFnl+MBWJBEvq+cL54cOH\na+6EYamtrW1V2N/fPzw8PCwszNfXNygoKCQkJCQkhKbpF7bLFRt2lLAmrdaRGvUl89cCC1fp\nvbA1+BSJ4OqR6Pn2mlmzZu3du/fEiROjRo365ZdfVqxYwa6n61QgrZaPJpwdgdjOE2hB3YTY\n1l2IWDN2797NMMzHH3/MPr/97rvvAgC7GksIMTTUzf3pFqbSNG1g8EzRy+VyKyurlvJKpVIq\nlTIMs2TJEmtr60WLFh08eNDM7MnYL8QYdh+AXC7XDMxZz2sVrryQtvCSmS9Qgjz2JTMfXZUP\nGDBAJBKlpzd/GOrXX3+lKOrWrVvsTxH3GMxf6UZGRurvXM9/REREsMsQR44ccXd39/PzAwCl\nUtnM+VXPvm6BK19dnRbpKnykJkLEaIoaaGracWawez0BQCwWx8XF3b59e/78+Xl5eVOmTGHv\nMV7YLtekh9B31ImNwLgDqwhAWy2wcJXeC1uDT3G0ECRGU/CSlXax1hg9erSDg8O+fft+/vln\npVKpXodtlw5Z3Ug5B0KJ5zhgtD2cTdEiM3uDngN0yptl9+7doaGhmtewYMGCEydOVFZWent7\nFxUVqWdHLl26RNN0UVGRTvr79++fm5urVsKWETsWAoDmHcyVK1cGDRp0+vTprVu3JiUlJScn\n79+/PyIigj0qxBhfX19CiPqtQoQQd3d39WRkS7jyQtrCK47TWr7lpBkUUFIDy/42wboq79Gj\nR3h4+JYtW+rr6zXTt27d2r9/f29vb60a2l7pb7zxhqGh4bFjx+Li4t5880020cfHJz8/v6Dg\nyYaPkpISdt1Ea766Oi3SVfibmbpIjGjQsjmfISTC1rod82XHZvW8nfqVjVu2bOnXr5+Xl9ey\nZcvi4+O3bdsWHx9PCHlhu1xaBE5CJjco6Okp8N5Tf/hrgYWr9F7YGnxKP0cwlWhragAMAT9X\nbUKtIxKJIiMjT5w4sWPHjkGDBqnHDv06ZK5Gyh3Yeb8htnbT4oaEkY6K1sNVL1++nJWV9fbb\nb2smzpkzR6FQxMbGTp06tU+fPosXLy4qKsrNzV2xYsWECRMcHBwAQCKRlJSUMFojToDw8HA3\nN7f58+fn5OSUlJSsXr26tLT0vffeY49++OGHGRkZ1dXVX331VUZGxooVK9jHUmQymUKhSE9P\nX7p0KQDI5XIhxgQHBwcGBkZHR9+9e7e0tHTlypXl5eVRUVFctnHlpWsxIpoMtJ/oZjmE4vVG\nAiTM/X8MaIke+jdv3iwSiUJDQ1NTUxsbG2Uy2ZIlS86ePbt7924hp7e90s3NzceNG7dly5aM\njIyZM2eyiVOnTnV3d1+wYEFubm5RUdHChQubLU9w5aur0yJdBQXwL9feDO8uAxqofsbGsx3s\n2jFfQ0NDd3f3vXv3lpWV5eTkrFq1ip2QnjhxokwmW79+fUVFRWFh4enTp4cOHUpR1Ivc5XoO\n17K+RVFA0+A5tL0y5ISnFrSW3otcg08Q0xA6SMuGHoqCXtYwoLfemcyaNauxsTE9PV3z9XX6\ndchcjZTbGWlRjynfUgbGPHGbxDfM2Ddc58sC+PHHH+3t7Zu9u2X48OFubm579+41MDA4efJk\nbW2tq6trQECAt7e3euycM2fO2bNn3d213x8ZGhqeOnWKpmkfHx8XF5eUlJRz586xvgUAy5cv\nnz59uq2tLbva3bt37+Dg4E8//TQqKsrS0nLp0qVr164NDQ2dNGlSWVmZVmMoijp58uTAgQOH\nDh3q6up648aNhIQER0dHLtu48tJ1VhLRhAJq8aCDUgMrnmdj/R3Cxri8q5/+nj17Xrt2zdvb\nOywsTCqVDh48uLy8/Nq1a/7+/kJOb5dKnzZt2u3bt1999VV1EzAwMDhx4kRTU5OHh4e/v39A\nQMCwYcOE5Pv48WOdnBbpQv5mbzvf0Z7rKA2UMU0f9vE0aO9/ZPnDDz8UFBQ4OTmNGzcuKiqK\nXZVzdXXdt2/f7t277e3tBw4cKBKJ2Kf8XuQu19QKBo4DAGh1soeigBDwCwUTYQt9bYGnFrSW\n3otcg08Z2R8GuXAepSgwMYT5wW35p7H+/v5eXl4ikUi98AIAuhaImlYbKcW//bCp5H5V3LtN\nZdkURT9Z56IoIAA0JQ1423TUe0AJ3diLIJ1AsfzB/12blludrumxFAGg4PXei2d6fy2i/sL/\nsrGqqsrGxiY2NjYsLKyrbUE6FYbARzm5X+Y9YoAAeTKnQAPFAHE3Nj7k4+krbCse0nHk34Hr\np6FJ8SSSgz9DOgMJ+IUKW65FngdUDMQlQ+JtULc0+LMue1rBgtfBzpzv9OcALYEdAACjarh1\nvOHumabiu0RZT5vaGboOMx44XWzd/OE7BHkeIIRJLoxNLvg5pyqtvqnKUtLTy/q1oF7ze5nr\nsxn0OUGlUimVyoMHD27YsOHmzZs8/2AD6cbck9fvKnz8S0XlI4XChKYHmJpOs7WeaW/b7nN1\niH401kNOOhQ9gNoKAAAzK3DoCy4DwECf3R9Il/KoHC5lwb0CqJSDsSE4W4GfK/i7tWWurtMQ\nENghCNLVyGSyPn36uLq67tmzZ8iQIV1tDoIgCPKcgoEdgiAIgiBIN6GDn71GEARBEARBOgsM\n7BAEQRAEQboJGNghCIIgCIJ0EzCwQxAEQRAE6SZgYIcgCIIgCNJNwMAOQRAEQRCkm4CBHYIg\nCIIgSDcBAzsEQRAEQZBuAgZ2CIIgCIIg3QQM7BAEQRAEQboJGNghCIIgCIJ0EzCwQxAEQRAE\n6SaIhQgpa/KqHx5tKMskyjqxqZO052umvcZQtEFHG4cg+lGgKD1afCGj9o/qpjoHI+uRloPG\nWw81Qo9F/uIoCTlXpjhXrihQqKQiytvUYLKtxMVYUDeOdA4KGam7TZTlBCgwsKakXpTRS1RX\nG4W8WFCEEJ7DjLKu6PdVFbd2EEYFFAVAAWEAwNDczem1baa9xnWWnQgiCAWjXPvHv7fIfm5k\nmiiKooFSEQYAXjKy3eK5MswuqKsNRBA9OVumiLpd8Ud9EwDQAASAAIgoeLun9CsPC1MRRg9d\njLKUFP/M1D8gAEBRAADs6GriQdlOow2ssIKQToJvKVbVWJV9+NXym98RRgUAQAgb1QFAY01O\nbnxoeeYOvTN2cXGhNLC2tv773/9eXV2tt8J2oampiaKoQ4cOtTzk6em5efPmzjcJEU49oxiT\n9u7G3P2NTBMAEEJUf3psQWPZlBvvf5W7ry36q6ur165d6+HhIZFIrKysJk+efOPGDfYQ6zlH\njx5teZZYLP7pp5/aki/L1atXvby8TE1N9dbJ497Ic84PBXXj0koeNjSxPxkA9o5cRWB7ft2w\nq8UVSkY/zZ6eniKRKCMjQzPx7bffHjx4MHSuz/yl/VMhI7JNqobsJxMlhIB6zkSeRfI3qRQF\nfHMoWtm/f39AQIClpaWtre3o0aMTEhL45durMHl6NuS5hS+we/Tr3PqS9NaPEYYQUnjhH/LC\nS3rnvWzZMkIIIUShUBw+fDg+Pv7dd9/VT9WoUaMWLVqktyVqxGIxIWTatGldaAOiN4vvfPVb\nxY1WDzGEASCr7287U3ZVP+VlZWXDhg07c+bMzp07KysrU1NTbWxshg0bdu3atTaYrANbtmyx\nsbGpqKjQW0Nb3BvpQpKrGhfcqiQADEdskFmnnJ1Zrrf+IUOGrFixotVDmj7T0V3cX9c/mXoo\n/I+KUainPp6FPBXQj6+//nrhwoWrV6/Ozc3NysoKDQ0dPXr03r17eU55DgsTh8hOgzOwq3uU\nWP3w2J+3ha1CCCFFvy1vuxGGhoajRo2KjIw8fvx427UhLybpNfd/KDjBI0AAKALv3d1E+Lya\nk+jo6JqamvPnzwcFBUkkEldX1127dvn5+XVaV1VbW9urVy8DA9wp+MKxMquK0ZgBagkhcKKk\n4deyBv30BwQEWFtb//e//9XTvheeivNMUw3faEkINFVC5QU9Z1V37Njx1ltvTZ061dzc3NLS\ncvny5ZGRkevWrdPTXKS7wxnYVd75Ufszs4SRP76qqMxqF1NUKpVUKmW/l5eXL1y40N7eXiqV\nDhgwYM+ePWx6aWnprFmzLCwsrKyswsLCcnNzAcDHx+fChQvbt2/v27cvADQ0NCxfvtzR0dHY\n2DggIEA9hywWi7/88svAwEBWrKysbN68edbW1hYWFmPGjGHnXTSnr3NyckJDQ01MTOzs7Nas\nWcMwT9pkq/oF2nDu3LlXXnnFxMTEysoqMjKypKSkXYoOAYDdhSdB2yYWBpi78tyUqju6Kq+o\nqDhw4EBUVJS5ubk6kaKoBQsWpKam5uTksCmZmZlBQUHGxsaOjo7r169vpqRVlwNhnjl48OBj\nx47t379fIpFo6mzV0zZt2kRR1C+//MLKhISEeHp6yuXyv/RS1wtLTn3TbxUKRtvdCE3BjwVy\nvXP58ssvP/roo6ampmbpap9p1sUJcVrg6PFycnIoitq9e3dgYKCJiYmvry/rt5r+2Uw/14jA\n1dN2KgRqrgmK2GpS9FyNNTIyunfvnnoMAoDRo0dnZ2fX1NToUZhcldXq8MrSas+mU6XgENmp\nEA6ydrvf/BaEfCpu/8ClhIfevXtrLsX++uuv5ubm69evZ1MiIiL8/f0fPnxYVVW1cuVKiqLy\n8/Obmpr8/PxGjx6dn59fVFQ0ZsyYIUOGsPIjR45855132O+TJ09+7bXXsrKyKioqtm/fLhaL\nT506RQgRiUS2trbnzp1TKpVNTU2DBw8eOXLk/fv3a2pq1q9fb2homJKSolQqASA2NlalUvn6\n+gYHBz948KCoqGjq1KkAsGnTJh79Wm0oLi42MTHZs2dPQ0NDdnZ2UFDQnDlz9Cg6pFWGXn2b\n+iUQBHw25/6kq/Jz584BQEJCApcA6zm2tranTp2qqan5f//v/wHAtWvXCCEikejAgQNcLkeE\neSYhZPLkyXPnzmWzY3USDk9jGCYoKMjFxaW2tvb777+nafrixYtqI2NjY/UoXqSr2F9YB2dk\nQj69LxTqod/Dw4Ptit9///0tW7awifPnz/f39yfP+oxmFyfEabl6vOzsbAB46aWXrl27JpfL\nt2/fTlHU77//rpmXpn7CMSIQ7t64M1GWk/vLlQI/TdX6ZHH+/Hl7e3t3d/cVK1YcPXq0uLhY\nfUjXwuSqLK7hladn07VScIjsNDgDu9s7LAUGdiWpG/TIuHfv3s1CTDc3t8zMTPaohYXFvn37\n2O/5+fkAcPHixfj4eADIyspi01NTUwEgLy+PaHhMSkoKAOTk5KgzCg0NnTFjBiFEJBLFxMSw\nifHx8RRFPXz4UC0WGBg4c+ZMdWM4fvw4TdOsckJIeXm5RCLZtGkTj36tNly5cgUAjh49qkdx\nIVpx+22KkKgOfgn85/3vdFXO3lBev36dS4D1nM8++0ydIpVKd+zYQf4MwrhcjgjzTNJaYMfj\njQ8fPjQ1NZ01a5alpeX777+vaSQGdn8tvs2tERjYSc/m66FfHdhVV1d7e3tXVFQQYYGdVqfl\n6vHYWEQdRBJCXn/99enTpzeLRdT6CceIwOP/nUmDjBEe2CkKGT1zaWiIi4ubN2+eg4MDRVEB\nAQHsfaauhclVWVzDK0/Ppmul4BDZaXC+AElsZK1qELRNW2RsLUSsJcuWLWOfM2UYJj8//6OP\nPgoMDLx586aLi0tFRUV9fX1aWppMJvvtt98AgBCSkpJiY2PTr18/9nQ/Pz/SYtcJ6xkuLi6a\niSNGjGC/sJPAAJCcnOzs7Ozq6qqWGTBggOYu+NTUVCcnJ2dnZ/anpaWlm5ubVv38Nvj7+4eH\nh4eFhfn6+gYFBYWEhISEhNA0viO6fbAxtMyuLxSyf87GwEJX5ZaWlgDw+PFjfjEPDw/1d4lE\nUldXp/7J73LCPVMTHm90dXXdsGFDVFSUr6/vJ598ovUCkecWawOhXYSVgagtGZmZmS1dujQm\nJmbjxo1C5LU6LX+PFxAQoJYfPHjwmTNnuPQDQKsjgpDeuBOgTXQS1vOlJ0ZGRuHh4eHh4QzD\nJCYmRkdHjx8//t69e+xR4YXJVVlcwyu7Ot9qz6Z3peAQ2dFwFpmxQyBFCSpQE/shbTWCpnv1\n6rVt27a6urqjR48yDLNkyRJra+tFixYdPHjQzMyMFSOEGBoa8qtiNxbI5XLN6JX1uWY5NtuE\nLpfLrays1D+VSmUzf1KpVAL1c8mIxeK4uLjbt2/Pnz8/Ly9vypQpkZGROhYVwkmAeX/eZ32e\nMqRHf12VDxgwQCQSpac3f0j8119/pSjq1q1b7E+RiHNk1epyOomx8Hsju/OvrKxMM75E/nK8\n0kNLp8dCUzDMQpAkD/Pnz79w4cKDBw90OovLafl7PCMjI015iuKMeLhGBIG9fUdjYEmJTAXI\nUSC2ALGZzvovXbpEUZS686FpOjg4ODY2VqFQJCYmsonCC5OrsviH15Y9W1sqBYfIjoYzdLPw\nnEVaf3T7KRRFG9sMNLLybhdTFAoFIcTAwOD06dNbt25NSkpKTk7ev39/REQEK+Dt7V1UVKSe\nNbl06RJN00VFRZpKfH19CSHJycnsT0KIu7t7y6eH+vfvn5ubq1bFepWfn59awMfHJz8/v6Cg\ngP1ZUlLCzngL0c8ls2XLln79+nl5eS1btiw+Pn7btm3x8fEtJx0R/fib4zitRUlTtKux09Ae\nProq79GjR3h4+JYtW+rr6zXTt27d2r9/f29v7U1Aq8vpJMbC442XLl3asGHDpk2bmpqaFi9e\nrMu1Is8X/UzEQ3oYap2LYwjMctRl7qg1RCLRF198sWbNGp3O4nJa/h5P8815ycnJL7/8Mpd+\nrhFBYG/f4VBg5kdrfXILCJj5CxBrga+vr0QiOXXqlGYiG8mpb/mEFyZXZQkZXjVpS6XgENnR\ncAZ2pr3GmTqPpbjdkAKKAHF49eu2G0EIefjw4d///ncrK6sZM2awz/3JZDKFQpGenr506VIA\nkMvlU6dO7dOnz+LFi4uKinJzc1esWDFhwgQHBwcAkEgkJSUlDMMEBwcHBgZGR0ffvXu3tLR0\n5cqV5eXlUVFRzXIMDw93c3ObP39+Tk5OSUnJ6tWrS0tL33vvPbXA1KlT3d3dFyxYkJubW1RU\ntHDhQta9ePRrtWHixIkymWz9+vUVFRWFhYWnT58eOnQoz60VohMBPbwjHcbwyxBCNnkso4VN\nRTdj8+bNIpEoNDQ0NTW1sbFRJpMtWbLk7Nmzu3fvFnK6VpfTSYyFy9PkcvncuXNHjx793nvv\nbd269cCBA7GxsXpcMvKc8JV7D8LTFwNQAMFWRhNtJdwiQhkzZkxDQ8OlS628oFTdxTVL53Ja\n/h7v448/zsjIqK6u/uKLL1JTU5csWcJlEteIILC37wQsX6dFJsBfQ2IzsHxNn57HzMzsww8/\njImJ2bVrV0VFRVVVVVJS0uzZs728vMaMedLjCS9MrsriGV5bRY9KwSGy0+DzM+dx+wwt+rXq\nrRRFEwCH4V9JX3pN77y/+eYb9t9O0DTNbtRNSkqysbEJDg7+9NNPo6KiLC0tly5dunbt2tDQ\n0EmTJpWVlZ08ebK2ttbV1TUgIMDb21s9ps6ZM+fs2bPu7u4URZ08eXLgwIFDhw51dXW9ceNG\nQkKCo6Njs6wNDQ1PnTpF07SPj4+Li0tKSsq5c+c0ndjAwODEiRNNTU0eHh7+/v4BAQHDhg0D\nAB79Wm1wdXXdt2/f7t277e3tBw4cKBKJ9u1r0z9CQJqxw+v9geburR5ig7mP3OZNttXzv4r1\n7Nnz2rVr3t7eYWFhUql08ODB5eXl7EYiIadrdTmdxFi4PG3VqlUFBQXbt28HgGnTpk2dOjUq\nKorn5ht5znnV0miThwVw9NcUBX2MxQde1nOvc0s2bNhw//79lunqLq5ZOpfT8vd4b7311ptv\nvmlvb88+rMb+o4tW4RoRHj9+LKS37wREpuDwlogWc8R2FNCG4PB3EW2sp/61a9du3759x44d\nPXv2dHZ2fvfdd8eOHXvp0iX1y4+EFyZXZRkYGHANr62iR6XgENlpaPlfsSpFZUHiP6qyfgIg\nQIkA2P9+x4hNHJxGbjHv+xy91RpBAKBOVb/s3qbvC/7LECKiaAAghDBArA3MN7ovm+sU2tUG\nIoiexD2uX3KnsrBRRT/5V6SUihAKYIaDyTYvC0vBz1h0OTk5Oa6urikpKTzxx18RRQEp/olR\nPCIUAKH/3PFLQOJM2b1JG9p3yMxTdy1MpC1oCexYGsoyqx/EKcoyGWWtWOpk6vy6mdtkWtzW\n/RwI0kFkyfMOPU7IqP2jUlnjZGQ70nJQuN1Ic7G0q+1CkDYhV5H4kvpzZYpHCpVURHmbGky1\nN/Y1/Yv9M5LuHIsQkN8n8jtEWUYAwMCGkvanjPvwrqO3je5cmIi+cL7uRBOJtY/EWuf95gjS\nVbib9Pqn69yutgJB2hkTERXpYBLpgDfVzysUmLhTJu64LQzpSgTN2CEIgiAIgiDPP3+ZbRkI\ngiAIgiAIPxjYIQiCIAiCdBMwsEMQBEEQBOkmYGCHIAiCIAjSTcDADkEQBEEQpJuAgR2CIAiC\nIEg3AQM7BEEQBEGQbgIGdgiCIAiCIN0EDOwQBEEQBEG6CRjYIQiCIAiCdBMwsEMQBEEQBOkm\nYGCHIAiCIAjSTRALkCHFsv8+zjlUU3mzSVkrMXnJ2jG4Z9+3JNKXOtw6BNGLX8qzDpak36gt\nrGpq6GlkHtTD7S2HwW7G1l1tF4K0iUf15Idccq6Eya8HUzH4mFNTe1KTHGmqqw1DnqAgTVfk\nqox6UqICCig7sehliTjQBAywipDOgyKE8Byur82+kTijsjSFApoAAwAURRPCiGijPoM+cfNd\nDYD+ijxHFDZWv3l734XKhxT1xLdpimIIMaDp952DP3YZS1Poschfkq/uMx/dUjUwQFPAEAAA\nGoAB8Legfg4QuUnRsbsYVWZD4/cVpFoFFAXkaQ1RFiLDv1uJvIy62kDkRYFvKVZe8+DS8SFV\nZakAwEZ1AEAIAwAM05iV+v7tK+92gok64enpuXnz5qamJoqiDh06xCXwnBjD0nYBXYmKijI2\nNlYoFOqUoKAgiqKys7PVKW+99ZapqalSqZw4cSKlgZmZ2ahRo5KTk9WS+/fvDwgIsLS0tLW1\nHT16dEJCglYD+vTp88MPP7TX5agpUFQPSf02qeohAKjvWBhCAEDJMDG5Z+fe/YkA350MD4GB\ngepCoGna0dFx/vz5hYWF/Ge1e909J4waNYrioKioiKKoo0ePdrWN3YoVN1WrbqoUBACeRHUA\nTzrl61XklfNNWbV6OrbWBt7u5OTkUBSVmZnZcVlw0XHtUXWtXrGllNSoAADIMzVEqlWKTSWq\n6/Vt0a9HN9sRdNcOrZvBGdgRwlw/P1XZWM5Gcs2PAgGAvLtbC7MPdqB1+iIWiwkh06ZN0+NI\neJKYAAATEElEQVTcUaNGLVq0qDONabuArgQHBzc0NKj77srKysuXLwPAyZMn1TJJSUmvvvqq\ngYEBAAwfPpwQQghhGCYrK8vKyiokJKS4uBgAvv7664ULF65evTo3NzcrKys0NHT06NF79+5t\nNV+lUnn79u0lS5Y8fPiwva5Fk5l39j1qrOKZg977OG1HwVW99U+YMIEtB4VCcfLkyYcPHwYG\nBhYVFfGc0u5195yQmJjIFgUb2n733XfkT2xsbLrauu5GXAHz9X0GNAIGTRgClU0w9YpKpWdo\nx9fAn3N07a47qD2SkibFf8qBQOu3jQxQAIpd5aRCpZ9+nbrZDkVIAQqplHYfZxFNOAO7opyf\naypuQGtRnRqKorNSP+DwZeT55bXXXqMoKikpif155swZlUrl7+9/4sQJNuXRo0fZ2dnBwcHN\nTqQoytHR8bPPPisvL79w4QIA7Nix46233po6daq5ubmlpeXy5csjIyPXrVvXar4ffPCBt7f3\n1q1bO+KizpTfu1D5kHdnAdAU9VH2mUZGz+5VjYGBwaBBg44fP15TU/PBBx+0URuC8PN+JsO/\njY4hkFlNDsj4umshtGzgiBCUJ2qgiW8xgBAAJVGerNFPv07dLIJwB3bZP1PanpklhKmvza4q\nTdEj49LS0lmzZllYWFhZWYWFheXm5rLp5eXlCxcutLe3l0qlAwYM2LNnD/w5/btt27axY8ca\nGxvb2dnFxMSw8jk5OaGhoSYmJnZ2dmvWrGEYBp6dLm5VgCsjHx+fCxcubN++vW/fvgDQ0NCw\nfPlyR0dHY2PjgIAAratL/MYEBwcHBASoha9du0ZR1O+//65p7blz51555RUTExMrK6vIyMiS\nkpJml1NWVjZv3jxra2sLC4sxY8Zcu3aNv3xaxcbGxtfXVx3YnThxws/Pb+7cuQkJCXK5HADY\nPv31119v9XSRSAQAFEUBgJGR0b1799SlCgCjR4/Ozs6uqWmlC/vqq68IIa0eajs/l9ygtO2f\nYwgpUdYmVj5olxxNTU1nz5598OBBpVIJHN6irjueOmq1ToG7jegq32p6bW1tswVTfifUlczM\nzKCgIGNjY0dHx/Xr17OJXA1KLBZ/+eWXgYGBffv2ZQtq06ZNI0eONDY27tu37/Hjx6Ojo11c\nXKRS6fTp01kX7Wj7nx/Sq8j9WsJou32mAQ7mtzWwY9Fs4K32k/BslYHuPgYAiYmJQ4YMMTMz\ne/nll9WJXNm1ql9gd93Su9jsuPLSGRVRpQpYZiWgSpGDXlXE081OmTLF19dXnX758mXNYaXV\nDkdIQQFAQUFBWFiYiYmJk5PTp59+6u3t/e9//1vraCWkUgRWXDdryJ0JZ+hWXX6dCPPB6vIb\nuuaqUqnGjRv3+PHjW7du3blzRy6XT58+nT20aNGitLS0K1euFBYWjh07du7cuY8ePWIPffTR\nR6tWrSorK4uJiVm3bl1ycjLDMJMmTVIoFJmZmTdv3nzw4MH9+/c1M+IRaDWjzMzMkSNHvvPO\nO3/88QcAREZGpqenJyUlFRYWzp8/PyIi4vTp01wXpdWYOXPmJCcny2Qy9ufBgwf79u07fPhw\ntUBJScmkSZOWLVtWUVGRlpZWWFi4cuXKZuU2fvz47Ozsq1ev5ufnjx07dvjw4epxvWX58FRB\ncHDwpUuXVCoVwzCnT58eP378+PHjGxoazp8/DwBJSUmWlpYDBw5sdhYhJDc39/3337exsWHD\nvs2bN9+8edPLy2vlypXHjh0rKSmZN28eIcTMzIwn944gvbaAf7pOzY26gvbK1MfHp76+/sGD\nByDMW1rWEVedcrURPeS52lqraHVCgXz77bf//Oc/S0pKPv/88zVr1qSmpvIX0caNGz///PO7\nd++yP7/44ouYmJiioiIfH59JkyYVFhampKSkpaWdPXt227ZtnWD/80NGlSC3ZgDSKtuaV8sG\nztMhq6tMVx9j2bBhw8aNG/Pz81lPYO8zW82OS7/w7rqZd7HwXJpuhVamIg2CxkpSx5BKfZYL\neLrZiIiIzMxMtgQAIC4urlevXsOGDWN/tjooCCkoQsjkyZNFIlF2dnZycvLVq1dv376taRJX\nQxNSKUJkul9D7lQIB2f3W576HoR8sjO/4lLCRXx8PABkZWWxP9lOPy8vjxBiYWGxb98+Nj0/\nPx8ALl68yM6I/Otf/1JrMDMz2759+/Hjx2maZk8khJSXl0skkk2bNrHysbGxXAJcGRFCWIcj\nhKSkpABATk6OOtPQ0NAZM2ZwXZRWY6qrq01MTNjcGYbp1atXTEwMIUQtcOXKFQA4evRoM81q\ngfj4eIqiHj58qD4UGBg4c+ZMrvLhqYLjx48DQHJyMru7jr32Pn36LFq0iBDi5eU1ZcoUVnLC\nhAmaDmNqajpixIiUlBS1qoaGhri4uHnz5jk4OFAUFRAQkJCQwJM1O2P3/fff88joQZ/LX0DC\nSiGftQ9P6aE/ICBAvcdOzbFjxwAgLS2Ny1vUdcdVR1x1ytVG9JBvNZ2thSNHjqj18DshFy33\n2LFX+tlnn6lTpFLpjh07eBqUSCRi24L69E8++YT9uXPnTgB49OgR+3PUqFFz584lf3pR2+1/\n/tnyhwoONwr5mB5r1EM/fwPn6ic1q0xXH2Mf0jpw4IA6/dVXX42IiODKjme8ENJdt/Su2NhY\nnkvTFVWOou5tmcCP6pE+dUS4u9mamhqJRLJ+/XpWrE+fPqtWrVJfacsOR2BBnTx5kqbp4uJi\n9mdRUZFIJPruu++0jlZEWKVolel+Dbkz4XyPnaGxo1JRKWT/nJGxo1aZZqSkpNjY2PTr14/9\n6efnR/6cbKmoqKivr09LS5PJZL/99htoPN7o5eWl1mBiYiKXy1NTU52cnJydndlES0tLNzc3\nzYx4BHgyYmEdy8XFRTNxxIgRXBel1RgzM7OwsLDDhw+/9957V65ckclks2fP1hTw9/cPDw8P\nCwvz9fUNCgoKCQkJCQmh6aezqsnJyc7Ozq6uruqUAQMGqGfsWpYPl6kAMHLkSLFYnJSUVFlZ\naWFhERgYCAAhISHs7eDdu3cXL16sFh4+fPjFixe5VBkZGYWHh4eHhzMMk5iYGB0dPX78+Hv3\n7iUkJMybN4+VOXDgQGRkJI89bcfJyDy7oUzIjbOToXl7ZVpVVQUA9vb2cXFxIMBbWtYRV51y\ntZEdO3boJL9z585W02tra1u9Ii4n/OGHH3SqTQ8PD/V3iURSV1fH36DYRZmWp4vFYpqmnZyc\n2J8ikaihoYEnX62N6C+Hg0SopKNEzzee8DRwnn5SXWVcvsflYyyDBw9Wfx8yZAi7VtBqdjzj\nhRqdvEvrpekE1UOkg7C5DsKacHWzvXv3Hjdu3JEjR1atWpWRkfHgwQPNttmywxFYUJmZmc7O\nzra2tuxPe3v7nj17ap4ipKEJGUO5ZLpfQ+5MOIvJ2uE1Ya+ooyztg3TNlRBiaGjYMp1hmCVL\nllhbWy9atOjgwYPNlvNaVqpSqWyWqFKphAjwZ8TCbiaQy+WagTDb/ltFqzEAMHv27EuXLhUW\nFh48ePC1117r3bu35lGxWBwXF3f79u358+fn5eVNmTKl2fBJ0zT7mKoauVxuZWWlPsplW0vM\nzMz8/f2TkpJOnDgxZswYdlfN+PHjZTLZtm3bCCFcG+w0uXTpEkVR6enpagOCg4NjY2MVCkVi\nYuJbb72lLreOjuoAYKRFH4HbV0Za9GmvTFNTU52dnR0dHQV6S8s64qpTrjaiqzxXejPUtwFc\nTqhrbbIepYlODcrI6OlLv7RunRRi/1+XV20EvXuRouA123Z+lZ2QfhJ09zEWzbagVCqlUilX\ndkL069pdC7w0IVAWIspWrH24pCjayYAy1Tk04e9mASAiIoJdUD5y5Ii7u7ufn5/63JYdjsCC\nqqioEIv5/n+BkIYmJC8ume7XkDsTTid7yf1t7Y4KtO1LIXr8Cwpvb++ioqLHjx+zPy9dukTT\ndFFR0enTp7du3ZqUlJScnLx///6IiAh+PT4+Pvn5+QUFT7ZMlZSUaL6JjUdASEa+vr6EEPVO\nNUKIu7s7z4NIWo0BgDFjxtjZ2R0+fDg2Nnbu3LnNjm7ZsqVfv35eXl7Lli2Lj4/ftm1bfHy8\n5k1k//79c3Nz1eXGNgDNZqwTwcHB58+fT09PDwkJYVNee+01iUSyceNGJycnT09PrRp8fX0l\nEsmpU6c0E9khWR1udhpvOQw20Bba0hQ9rEdvb6l9u+RYVVW1f//+WbNmURSlq7eo4apTrjai\nqzxXOjtSqudUbtx4slNWqxPqjd5F1Cqdb39XYW8Ek4X8bwkCC1zaeT5DYIesq4+xqJcaAODK\nlSuDBg3iyo5Lv6Y2Xb1L17GGH/FIqfbFLULEI6V6KNfazb7xxhuGhobHjh2Li4t78803tWoT\nUlCurq4ymYxdkQCAvLw89e5wFiENTUheXDLdryF3JpwdgbnVQGcP3tfMUDQtNvZ8ZaMeuU6d\nOrVPnz6LFy8uKirKzc1dsWLFhAkTHBwcJBIJAMhkMoVCkZ6evnTpUmhxn9dMj7u7+4IFC3Jz\nc4uKihYuXNis4rkEeDKSSCQlJSUMwwQHBwcGBkZHR9+9e7e0tHTlypXl5eVRUVF6GwMAIpFo\n5syZMTEx1dXVU6dObXZ04sSJMpls/fr1FRUVhYWFp0+fHjp0qOZ0RXh4uJub2/z583NyckpK\nSlavXl1aWvree+8JKvQWBAcH19bWEkLGjx/PppiYmAQFBdXU1LR80UmrmJmZffjhhzExMbt2\n7aqoqKiqqkpKSpo9e7aXl9eYMWP0s0pv+hhbr3J+jUeApigxRX3bN6zteSkUimvXroWEhFha\nWrKvO9HVW9Rw1SlXG9FVnivd0NDQ3d197969ZWVlOTk5q1atYufYtDqh3uhdRK3S+fZ3Iet9\naKkY+IO7Ba70YMt2vkyBHbKuPsby4YcfZmRkVFdXf/XVVxkZGStWrODKjks/tKG71nWs4ccg\n2JR2NOB7jQQFtLOBOEifwE5rN2tubj5u3LgtW7ZkZGTMnDmTX5vAggoPD5dKpUuXLi0rK8vN\nzf373//eTICnoQmpFK0y3bIhdxp8d3ieQzbbOU8EAKrlLDNF07TRwFE/S3ton9dpiYGBwcmT\nJ2tra11d/3979xPSyBXAcXxmEs02bq3WaKoiMbXGLQZNEQwiWpsWpR4khSC0h9w8BKoFrylF\n7MGDoLK9VE8SzUFCe4tS/1QQlIKXWksQulKK6IJd26arZGkSp4eAuN3m39R/fXw/x+ExM5k/\nb355780bq9PpbGxsDAQCkiS5XK7R0VGfz1daWjo0NOT3+3t7e/v6+tLNAVtQUBAOhxOJREND\nQ0tLi9PpvHgbKHOBDBvyer2rq6s2m02W5cXFRYfD0dbWZrVad3Z21tfXKyvTDijMujMpXq/3\n+PjY4/EUFf3zJrdarcFgMBAImM1mh8Oh0+mCweDlAoWFhUtLS4qi2O322tra7e3ttbW1VAWn\nQXt7u8FgaG5uvvyjUq13OQY7SZL8fv/09PTMzEx1dXVNTc3g4GB3d/fW1laq3rxho7XdH5nf\nkiRJeeGKVWRFLytzDz5seVn7N47D4XBqdn6j0eh2u5uamjY3N1OdOPleLRfSndN090i+5dMt\nlyRpdnb26Oioqqqqp6fH5/Ol/v1nvQg103yI0rnh/b9F9fflr5z6e8q/ZLvUk+791+SHzRoH\nb2WQY4Wc7zWWMjw83N/fX15ePj8/Hw6HLRZLus2dnJykW7/m6jrfZ00WBbJhsEx+NU3fpSwp\nFXrDxyZJrzGXZK1mPR5PJBLp6Oiw2WyZV5XjgTKZTBsbG4eHhxaLxel0ulwus9lsNBovCmS4\n0XI5KVnLCHkj35gs34pV1fNfIpOPvv88EY9eXl5W+c6brQ/vl9qvefeA/KiS+uXRd5/9/M2T\n+Nnl5W2vWL54w/1fUh1wuyJ/qp/8kFw9fq7GLtZLnz7QDdcrOtoybpt6eh7/OprYPHtuojBF\n1ncWFXxQLBuvceB/NBo1mUyhUMjtvoIeiRfFYrGSkpKVlZXOzryH1OPmZQl2Kclk7LfH3z79\nfTcZPzUYq8uq3i0qzvK3QGDpWoMnJyc194pek//Rrl6tv86T63882jl9HE0+qyosfrvkdXuR\nxnZN4E756VRd+1U9jKlGnWwvlt6rUF66+qY6aKc+PU/++Ex9kpAkSa7Q6xrvaXhhInfJZDIe\njy8sLIyPj+/u7l5VZ+X+/n59ff3U1NTAwMDZ2dnIyMjy8nIkEsn8RgXuiJyCHQAAuGsODg7q\n6uqsVuvc3Fxra+sVrjkUCo2Nje3t7RkMhq6uromJicuzLOEuI9gBAAAIgun+AAAABEGwAwAA\nEATBDgAAQBAEOwAAAEEQ7AAAAARBsAMAABAEwQ4AAEAQBDsAAABBEOwAAAAEQbADAAAQBMEO\nAABAEAQ7AAAAQRDsAAAABEGwAwAAEATBDgAAQBAEOwAAAEEQ7AAAAARBsAMAABAEwQ4AAEAQ\nBDsAAABBEOwAAAAEQbADAAAQBMEOAABAEH8D9YLplBiBw5EAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p2 <- plot.threshold(est.obj = as.threshold, x= \"P\", y= \"RA\", taxrank = \"Phylum\", PFT = 2, RAT = 6e-5)\n",
    "\n",
    "p2 + ggplot2::theme(legend.position = \"bottom\",\n",
    "                         strip.text = element_text(size=8, color=\"white\")) + \n",
    "ggplot2::guides(color=guide_legend(title.position = \"top\", title.hjust = 0.5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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WzZMrlcnpWVVVpaumrVKgB4YYfcxhpobtSdjAA01UGToMbkzYeQwsLCjz/+2N7e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\nelcz9a7AYZg4cSJFURRFtWrV6ujRo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R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\ntznDStMv5BUU22zrunRu4FMAoIwg/1N64wed3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y7Fi2F3/Pjxb775ZtSoURMnTnzttdfUajUAvP/++yNHjgwPD2dZtnv37r/++mvDs5iX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CR2Pujq1atr166V9dBxL2/IP3VO9yKIboXBCACd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\nEtIAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p3 <- plot.threshold(est.obj = as.threshold, x= \"CV\", y= \"RA\", taxrank = \"Phylum\", CVT = 0, RAT = 6e-5)\n",
    "\n",
    "p3 + ggplot2::theme(legend.position = \"top\",\n",
    "                         strip.text = element_text(size=8, color=\"white\")) + \n",
    "ggplot2::guides(color=guide_legend(title.position = \"bottom\", title.hjust = 0.5))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\">\n",
    "<b>Commentary:</b> You might notice that I only chose to apply relative abundance and prevalence filters. \n",
    "While I think that all three have their associated merits, CV calculations and filters are particularly \n",
    "susceptible to compositional effects. <b>Prior to estimation and application of CV parameters, estimate.ASthreshold normalizes each sample to the median sequencing depth of the dataset, but this still does not properly account \n",
    "for the compositional nature of marker gene studies.</b> <i>With that said, you should feel free to apply \n",
    "whatever approaches that you feel are appropriate!</i>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"filter.dataset\"></a>\n",
    "# microfilter\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>MICROFILTER</b><br>\n",
    "A highly flexible function capable of applying any combination of WS and AS (relative abundance, prevalence, CV) taxonomic filters, as well as metadata (positive and negative) and read count based sample filters. <br>\n",
    "<br>\n",
    "<b>Input:</b> <br>\n",
    "<b>ps:</b> a phyloseq-class dataset.<br>\n",
    "<br>\n",
    "<b>Parameters (all are optional):</b><br>\n",
    "<b>controlID:</b> As above, used only for reporting ASV read count, taxonomy, and sequence identity of taxa in the positive control.<br>\n",
    "<b>mdCAT:</b> The sample data category used in conjunction with mdFACTOR for metadata based filtering.<br>\n",
    "<b>mdFACTOR:</b> The factor within mdCAT used for metadata based filtering.<br>\n",
    "<b>mdNEGATIVE:</b> A logical flag indicating whether metadata-based filtering should be positive (remove matching samples) or negative (remove non matching samples).<br>\n",
    "<b>minLIB:</b> The minimum sequence depth for a sample to be retained.<br>\n",
    "<b>RAT:</b> Relative Abundance Threshold; the percentage of reads across the dataset for which an ASV must be present for that ASV to be retained. <br>\n",
    "<b>CVT:</b> Coefficient of Variation Threshold; the lowest CV value of an ASV for that ASV to be retained.<br>\n",
    "<b>PFT:</b> Prevalence Filter Threshold; the percentage of samples across the dataset for which an ASV must be present for that ASV to be retained. <br>\n",
    "<b>return.all:</b> A logical flag indicating whether to return all output or only the filtered dataset. Default is FALSE.<br>\n",
    "<br><br>\n",
    "<b>Output:</b> <br>\n",
    "<b>control.taxa.sequences</b>\n",
    "-  These are the nucleotide sequences of the taxa remaining in the positive control after applying the within-sample filter threshold. Useful for cross referenceing annotations against additional databases.<br>\n",
    "<b>taxonomy.of.control.taxa</b>\n",
    "-   The taxonomy of taxa in the positive control are output in the same order as the sequences, above. Generally useful for validating that the bugs detected in your mock community are as intended. <br>\n",
    "<b>read.count.table</b>\n",
    "-  This table lists the read count and percentage remaining after each filtering step. Samples matching given metadata identifiers are removed after application of the WS filter and prior to the AS filter(s) and, as such, will list NA values for AS filter statistics.  <br>\n",
    "<b>relative abundance.filter.threshold</b>\n",
    "-  The read count corresponding to the percentage given to the RAT parameter. <br>\n",
    "<b>prevalence.filter.threshold</b>\n",
    "-  The sample count corresponding to the percentage given to the PFT parameter. <br>\n",
    "<b>filtered.phyloseq</b>\n",
    "-  the shiny new (phyloseq class) filtered dataset with control samples removed. <br>\n",
    "\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we've estimated our WS and AS filtering thresholds, we can apply these thresholds to our dataset with the __microfilter__ function. Due to the multifacted nature of the function, we'll also simultaneously remove samples with less than 1000 reads and those that are flagged as controls by metadata identifiers. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Removing 27 samples with read count < 1000\n",
      "Applying WS filter threshold of 0.00065\n",
      "Removing 4 samples matching metadata identifiers Visit:Mock\n",
      "Applying relative abundance threshold of 6e-05\n",
      "Applying prevalence threshold of 0.02\n"
     ]
    }
   ],
   "source": [
    "e3.f <- microfilter(ps = e3, WST = 6.5e-4, PFT = 0.02, RAT = 6e-5, minLIB = 1000, mdFACTOR = \"Mock\", mdCAT = \"Visit\", controlID = \"185\", return.all = TRUE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "25"
      ],
      "text/latex": [
       "25"
      ],
      "text/markdown": [
       "25"
      ],
      "text/plain": [
       "[1] 25"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "e3.f$ntaxa.in.control"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>'TAGGGAATCTTCGGCAATGGACGAAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTAAGTCAAGAACGTGTGTGAGAGTGGAAAGTTCACACAGTGACGGTAGCTTACCAGAAAGGGACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTCCCGAGCGTTGTCCGGATTTATTGGGCGTAAAGGGAGCGCAGGCGGTCAGGAAAGTCTGGAGTAAAAGGCTATGGCTCAACCATAGTGTGCTCTGGAAACTGTCTGACTTGAGTGCAGAAGGGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCAGTGGCGAAAGCGGCTCTCTGGTCTGTCACTGACGCTGAGGCTCGAAAGCGTGGGTAGCGAACAGG'</li>\n",
       "\t<li>'TGGGGAATATTGCACAATGGGCGCAAGCCTGATGCAGCCATGCCGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAAGGGAGTAAAGTTAATACCTTTGCTCATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGCACGCAGGCGGTTTGTTAAGTCAGATGTGAAATCCCCGGGCTCAACCTGGGAACTGCATCTGATACTGGCAAGCTTGAGTCTCGTAGAGGGGGGTAGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCGAAGGCGGCCCCCTGGACGAAGACTGACGCTCAGGTGCGAAAGCGTGGGGAGCAAACAGG'</li>\n",
       "\t<li>'TAGGGAATCTTCCGCAATGGGCGAAAGCCTGACGGAGCAACGCCGCGTGAGTGATGAAGGTCTTCGGATCGTAAAACTCTGTTATTAGGGAAGAACAAATGTGTAAGTAACTATGCACGTCTTGACGGTACCTAATCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGCGCGTAGGCGGTTTTTTAAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGAAAACTTGAGTGCAGAAGAGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGCAGAGATATGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACGCTGATGTGCGAAAGCGTGGGGATCAAACAGG'</li>\n",
       "\t<li>'TAGGGAATCTTCCACAATGGACGCAAGTCTGATGGAGCAACGCCGCGTGAGTGAAGAAGGGTTTCGGCTCGTAAAGCTCTGTTGGTAGTGAAGAAAGATAGAGGTAGTAACTGGCCTTTATTTGACGGTAATTACTTAGAAAGTCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGTGCAGGCGGTTCAATAAGTCTGATGTGAAAGCCTTCGGCTCAACCGGAGAATTGCATCAGAAACTGTTGAACTTGAGTGCAGAAGAGGAGAGTGGAACTCCATGTGTAGCGGTGGAATGCGTAGATATATGGAAGAACACCAGTGGCGAAGGCGGCTCTCTGGTCTGCAACTGACGCTGAGGCTCGAAAGCATGGGTAGCGAACAGG'</li>\n",
       "\t<li>'TGGGGAATCTTAGACAATGGGCGCAAGCCTGATCTAGCCATGCCGCGTGATCGATGAAGGCCTTAGGGTTGTAAAGATCTTTCAGGTGGGAAGATAATGACGGTACCACCAGAAGAAGCCCCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGGGCTAGCGTTATTCGGAATTACTGGGCGTAAAGCGCACGTAGGCGGATCGGAAAGTCAGAGGTGAAATCCCAGGGCTCAACCCTGGAACTGCCTTTGAAACTCCCGATCTTGAGGTCGAGAGAGGTGAGTGGAATTCCGAGTGTAGAGGTGAAATTCGTAGATATTCGGAGGAACACCAGTGGCGAAGGCGGCTCACTGGCTCGATACTGACGCTGAGGTGCGAAAGCGTGGGGAGCAAACAGG'</li>\n",
       "\t<li>'TGGGGAATATTGGACAATGGGCGAAAGCCTGATCCAGCCATGCCGCGTGTGTGAAGAAGGTCTTCGGATTGTAAAGCACTTTAAGTTGGGAGGAAGGGCAGTAAGTTAATACCTTGCTGTTTTGACGTTACCAACAGAATAAGCACCGGCTAACTTCGTGCCAGCAGCCGCGGTAATACGAAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGCGCGTAGGTGGTTCAGCAAGTTGGATGTGAAATCCCCGGGCTCAACCTGGGAACTGCATCCAAAACTACTGAGCTAGAGTACGGTAGAGGGTGGTGGAATTTCCTGTGTAGCGGTGAAATGCGTAGATATAGGAAGGAACACCAGTGGCGAAGGCGACCACCTGGACTGATACTGACACTGAGGTGCGAAAGCGTGGGGAGCAAACAGG'</li>\n",
       "\t<li>'TGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCAACGCCGCGTGAGTGATGACGGTCTTCGGATTGTAAAGCTCTGTCTTCAGGGACGATAATGACGGTACCTGAGGAGGAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTACTGGGCGTAAAGGGAGCGTAGGTGGATATTTAAGTGGGATGTGAAATACTCGGGCTTAACCTGGGTGCTGCATTCCAAACTGGATATCTAGAGTGCAGGAGAGGAAAGTAGAATTCCTAGTGTAGCGGTGAAATGCGTAGAGATTAGGAAGAATACCAGTGGCGAAGGCGACTTTCTGGACTGTAACTGACACTGAGGCTCGAAAGCGTGGGGAGCAAACAGG'</li>\n",
       "\t<li>'TAGGGAATCTTCGGCAATGGACGGAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTTAGAGAAGAACGTTGGTAGGAGTGGAAAATCTACCAAGTGACGGTAACTAACCAGAAAGGGACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTCCCGAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGCGCAGGCGGTTCTTTAAGTCTGAAGTTAAAGGCAGTGGCTTAACCATTGTACGCTTTGGAAACTGGAGGACTTGAGTGCAGAAGGGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCGGTGGCGAAAGCGGCTCTCTGGTCTGTAACTGACGCTGAGGCTCGAAAGCGTGGGGAGCAAACAGG'</li>\n",
       "\t<li>'TAGGGAATATTGCTCAATGGGGGAAACCCTGAAGCAGCAACGCCGCGTGGAGGATGAAGGTTTTAGGATTGTAAACTCCTTTTGTTAGAGAAGATAATGACGGTATCTAACGAATAAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTACTCGGAATCACTGGGCGTAAAGAGCGCGTAGGCGGGATAGTCAGTCAGGTGTGAAATCCTATGGCTTAACCATAGAACTGCATTTGAAACTACTATTCTAGAGTGTGGGAGAGGTAGGTGGAATTCTTGGTGTAGGGGTAAAATCCGTAGAGATCAAGAGGAATACTCATTGCGAAGGCGACCTGCTGGAACATTACTGACGCTGATTGCGCGAAAGCGTGGGGAGCAAACAGG'</li>\n",
       "\t<li>'TGGGGAATTTTGGACAATGGGCGCAAGCCTGATCCAGCCATGCCGCGTGTCTGAAGAAGGCCTTCGGGTTGTAAAGGACTTTTGTCAGGGAAGAAAAGGCTGTTGCTAATATCAGCGGCTGATGACGGTACCTGAAGAATAAGCACCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGTGCGAGCGTTAATCGGAATTACTGGGCGTAAAGCGGGCGCAGACGGTTACTTAAGCAGGATGTGAAATCCCCGGGCTCAACCCGGGAACTGCGTTCTGAACTGGGTGACTCGAGTGTGTCAGAGGGAGGTAGAATTCCACGTGTAGCAGTGAAATGCGTAGAGATGTGGAGGAATACCGATGGCGAAGGCAGCCTCCTGGGACAACACTGACGTTCATGCCCGAAAGCGTGGGTAGCAAACAGG'</li>\n",
       "\t<li>'TTAGGAATCTTCCACAATGGGCGCAAGCCTGATGGAGCGACGCCGCGTGAGGGATGAAGGTTTTCGGATCGTAAACCTCTGAATCTGGGACGAAAGAGCCTTAGGGCAGATGACGGTACCAGAGTAATAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTACCCGGAATCACTGGGCGTAAAGGGCGTGTAGGCGGAAATTTAAGTCTGGTTTTAAAGACCGGGGCTCAACCTCGGGGATGGACTGGATACTGGATTTCTTGACCTCTGGAGAGGTAACTGGAATTCCTGGTGTAGCGGTGGAATGCGTAGATACCAGGAGGAACACCAATGGCGAAGGCAAGTTACTGGACAGAAGGTGACGCTGAGGCGCGAAAGTGTGGGGAGCAAACCGG'</li>\n",
       "\t<li>'TGGGGAATATTGGACAATGGGGGGAACCCTGATCCAGCCATGCCGCGTGTGTGAAGAAGGCCTTATGGTTGTAAAGCACTTTAAGCGAGGAGGAGGCTACTTTAGTTAATACCTAGAGATAGTGGACGTTACTCGCAGAATAAGCACCGGCTAACTCTGTGCCAGCAGCCGCGGTAATACAGAGGGTGCGAGCGTTAATCGGATTTACTGGGCGTAAAGCGTGCGTAGGCGGCTTATTAAGTCGGATGTGAAATCCCCGAGCTTAACTTGGGAATTGCATTCGATACTGGTGAGCTAGAGTATGGGAGAGGATGGTAGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGATGGCGAAGGCAGCCATCTGGCCTAATACTGACGCTGAGGTACGAAAGCATGGGGAGCAAACAGG'</li>\n",
       "\t<li>'TGAGGAATATTGGTCAATGGGCGAGAGCCTGAACCAGCCAAGTAGCGTGAAGGATGACTGCCCTATGGGTTGTAAACTTCTTTTATAAAGGAATAAAGTCGGGTATGGATACCCGTTTGCATGTACTTTATGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGAGCGTAGATGGATGTTTAAGTCAGTTGTGAAAGTTTGCGGCTCAACCGTAAAATTGCAGTTGATACTGGATATCTTGAGTGCAGTTGAGGCAGGCGGAATTCGTGGTGTAGCGGTGAAATGCTTAGATATCACGAAGAACTCCGATTGCGAAGGCAGCCTGCTAAGCTGCAACTGACATTGAGGCTCGAAAGTGTGGGTATCAAACAGG'</li>\n",
       "\t<li>'TAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGCCGCGTGAGTGATGAAGGCTTTCGGGTCGTAAAACTCTGTTGTTAGGGAAGAACAAGTGCTAGTTGAATAAGCTGGCACCTTGACGGTACCTAACCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGCGCGCAGGTGGTTTCTTAAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGGAGACTTGAGTGCAGAAGAGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGAGATATGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACACTGAGGCGCGAAAGCGTGGGGAGCAAACAGG'</li>\n",
       "\t<li>'TAGGGAATCTTCCGCAATGGGCGAAAGCCTGACGGAGCAACGCCGCGTGAGTGATGAAGGTCTTCGGATCGTAAAACTCTGTTATTAGGGAAGAACATATGTGTAAGTAACTGTGCACATCTTGACGGTACCTAATCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGCGCGTAGGCGGTTTTTTAAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGAAAACTTGAGTGCAGAAGAGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGCAGAGATATGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACGCTGATGTGCGAAAGCGTGGGGATCAAACAGG'</li>\n",
       "\t<li>'TAGGGAATCTTCCGCAATGGGCGAAAGCTTGACGGAGCAACGCCGCGTGAGTGATGAAGGTCTTCGGATCGTAAAACTCTGTTATTAGGGAAGAACAAATGTGTAAGTAACTATGCACGTCTTGACGGTACCTAATCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGCGCGTAGGCGGTTTTTTAAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGAAAACTTGAGTGCAGAAGAGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGCAGAGATATGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACGCTGATGTGCGAAAGCGTGGGGATCAAACAGG'</li>\n",
       "\t<li>'TAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGCCGCGTGTATGAAGAAGGTTTTCGGATCGTAAAGTACTGTTGTTAGAGAAGAACAAGGATAAGAGTAACTGCTTGTCCCTTGACGGTATCTAACCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGCGCGCAGGCGGTCTTTTAAGTCTGATGTGAAAGCCCCCGGCTTAACCGGGGAGGGTCATTGGAAACTGGAAGACTGGAGTGCAGAAGAGGAGAGTGGAATTCCACGTGTAGCGGTGAAATGCGTAGATATGTGGAGGAACACCAGTGGCGAAGGCGACTCTCTGGTCTGTAACTGACGCTGAGGCGCGAAAGCGTGGGGAGCAAACAGG'</li>\n",
       "\t<li>'TGGGGAATATTGCACAATGGGCGGAAGCCTGATGCAGCAACGCCGCGTGCGGGATGACGGCCTTCGGGTTGTAAACCGCTTTCGCCTGTGACGAAGCGTGAGTGACGGTAATGGGTAAAGAAGCACCGGCTAACTACGTGCCAGCAGCCGCGGTGATACGTAGGGTGCGAGCGTTGTCCGGATTTATTGGGCGTAAAGGGCTCGTAGGTGGTTGATCGCGTCGGAAGTGTAATCTTGGGGCTTAACCCTGAGCGTGCTTTCGATACGGGTTGACTTGAGGAAGGTAGGGGAGAATGGAATTCCTGGTGGAGCGGTGGAATGCGCAGATATCAGGAGGAACACCAGTGGCGAAGGCGGTTCTCTGGGCCTTTCCTGACGCTGAGGAGCGAAAGCGTGGGGAGCGAACAGGC'</li>\n",
       "\t<li>'TAGGGAATCTTCGGCAATGGACGAAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAACTCTGTTGTTAGAGAAGAACAAGGACGTTAGTAACTGAACGTCCCCTGACGGTATCTAACCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGCGCAGGCGGTTTCTTAAGTCTGATGTGAAAGCCCCCGGCTCAACCGGGGAGGGTCATTGGAAACTGGGAGACTTGAGTGCAGAAGAGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCAGTGGCGAAGGCGGCTCTCTGGTCTGTAACTGACGCTGAGGCTCGAAAGCGTGGGGAGCAAACAGG'</li>\n",
       "\t<li>'TGAGGAATATTGGTCAATGGGCGAGAGCCTGAACCAGCCAAGTAGCGTGAAGGATGACTGCCCTATGGGTTGTAAACTTCTTTTATAAAGGAATAAAGTCGGGTATGGATACCCGTTTGCATGTACTTTATGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGAGCGTAGATGGATATTTAAGTCAGTTGTGAAAGTTTGCGGCTCAACCGTAAAATTGCAGTTGATACTGGATATCTTGAGTGCAGTTGAGGCAGGCGGAATTCGTGGTGTAGCGGTGAAATGCTTAGATATCACGAAGAACTCCGATTGCGAAGGCAGCCTGCTAAGCTGCAACTGACATTGAGGCTCGAAAGTGTGGGTATCAAACAGG'</li>\n",
       "\t<li>'TGGGGAATATTGCACAATGGGCGAAAGCCTGATGCAGCGACGCCGCGTGAGGGATGGAGGCCTTCGGGTTGTAAACCTCTTTCGCTCATGGTCAAGCCGCAACTCAAGGTTGTGGTGAGGGTAGTGGGTAAAGAAGCGCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGCGCGAGCGTTGTCCGGAATTATTGGGCGTAAAGGGCTTGTAGGCGGTTGGTCGCGTCTGCCGTGAAATCCTCTGGCTTAACTGGGGGCGTGCGGTGGGTACGGGCTGACTTGAGTGCGGTAGGGGAGACTGGAACTCCTGGTGTAGCGGTGGAATGCGCAGATATCAGGAAGAACACCGGTGGCGAAGGCGGGTCTCTGGGCCGTTACTGACGCTGAGGAGCGAAAGCGTGGGGAGCGAACAGG'</li>\n",
       "\t<li>'TGAGGAATATTGGTCAATGGGCGCAGGCCTGAACCAGCCAAGTAGCGTGAAGGATGACTGCCCTATGGGTTGTAAACTTCTTTTATAAAGGAATAAAGTCGGGTATGGATACCCGTTTGCATGTACTTTATGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGAGCGTAGATGGATGTTTAAGTCAGTTGTGAAAGTTTGCGGCTCAACCGTAAAATTGCAGTTGATACTGGATATCTTGAGTGCAGTTGAGGCAGGCGGAATTCGTGGTGTAGCGGTGAAATGCTTAGATATCACGAAGAACTCCGATTGCGAAGGCAGCCTGCTAAGCTGCAACTGACATTGAGGCTCGAAAGTGTGGGTATCAAACAGG'</li>\n",
       "\t<li>'TGAGGAATATTGGTCAATGGGCGAGAGCCTGAACCAGCCAAGTAGCGTGAAGGATGACTGCCCTATGGGTTGTAAACTTCTTTTATAAAGGAATAAAGTCGGGTATGCATACCCGTTTGCATGTACTTTATGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGAGCGTAGATGGATGTTTAAGTCAGTTGTGAAAGTTTGCGGCTCAACCGTAAAATTGCAGTTGATACTGGATATCTTGAGTGCAGTTGAGGCAGGCGGAATTCGTGGTGTAGCGGTGAAATGCTTAGATATCACGAGGAACTCCGATTGCGAAGGCAGCCTGCTAAGCTGCAACTGACATTGAGGCTCGAAAGTGTGGGTATCAAACAGG'</li>\n",
       "\t<li>'TAGGGAATCTTCGGCAATGGACGGAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTAAGAGAAGAACGAGTGTGAGAGTGGAAAGTTCACACTGTGACGGTATCTTACCAGAAAGGGACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTCCCGAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGCGCAGGCGGTTAGATAAGTCTGAAGTTAAAGGCTGTGGCTTAACCATAGTAGGCTTTGGAAACTGTTTAACTTGAGTGCAAGAGGGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCGGTGGCGAAAGCGGCTCTCTGGCTTGTAACTGACGCTGAGGCTCGAAAGCGTGGGGAGCAAACAGG'</li>\n",
       "\t<li>'TGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCAACGCCGCGTGAGTGATGACGGTCTTCGGATTGTAAAGCTCTGTCTTCAGGGACGATAATGACGGTACCTGAGGAGGAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTACTGGGCGTAAAGGGAGCGTAGGTGGATATTTAAGTGGGATGTGAAATACTCGGGCTTAACCTGGGTGCTGCATTCCAAACTGGATATCTAGAGTGCAGGAGAGGAAAGTAGAATTCTTAGTGTAGCGGTGAAATGCGTAGAGATTAGGAAGAATACCAGTGGCGAAGGCGACTTTCTGGACTGTAACTGACACTGAGGCTCGAAAGCGTGGGGAGCAAACAGG'</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'TAGGGAATCTTCGGCAATGGACGAAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTAAGTCAAGAACGTGTGTGAGAGTGGAAAGTTCACACAGTGACGGTAGCTTACCAGAAAGGGACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTCCCGAGCGTTGTCCGGATTTATTGGGCGTAAAGGGAGCGCAGGCGGTCAGGAAAGTCTGGAGTAAAAGGCTATGGCTCAACCATAGTGTGCTCTGGAAACTGTCTGACTTGAGTGCAGAAGGGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCAGTGGCGAAAGCGGCTCTCTGGTCTGTCACTGACGCTGAGGCTCGAAAGCGTGGGTAGCGAACAGG'\n",
       "\\item 'TGGGGAATATTGCACAATGGGCGCAAGCCTGATGCAGCCATGCCGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAAGGGAGTAAAGTTAATACCTTTGCTCATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGCACGCAGGCGGTTTGTTAAGTCAGATGTGAAATCCCCGGGCTCAACCTGGGAACTGCATCTGATACTGGCAAGCTTGAGTCTCGTAGAGGGGGGTAGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCGAAGGCGGCCCCCTGGACGAAGACTGACGCTCAGGTGCGAAAGCGTGGGGAGCAAACAGG'\n",
       "\\item 'TAGGGAATCTTCCGCAATGGGCGAAAGCCTGACGGAGCAACGCCGCGTGAGTGATGAAGGTCTTCGGATCGTAAAACTCTGTTATTAGGGAAGAACAAATGTGTAAGTAACTATGCACGTCTTGACGGTACCTAATCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGCGCGTAGGCGGTTTTTTAAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGAAAACTTGAGTGCAGAAGAGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGCAGAGATATGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACGCTGATGTGCGAAAGCGTGGGGATCAAACAGG'\n",
       "\\item 'TAGGGAATCTTCCACAATGGACGCAAGTCTGATGGAGCAACGCCGCGTGAGTGAAGAAGGGTTTCGGCTCGTAAAGCTCTGTTGGTAGTGAAGAAAGATAGAGGTAGTAACTGGCCTTTATTTGACGGTAATTACTTAGAAAGTCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGTGCAGGCGGTTCAATAAGTCTGATGTGAAAGCCTTCGGCTCAACCGGAGAATTGCATCAGAAACTGTTGAACTTGAGTGCAGAAGAGGAGAGTGGAACTCCATGTGTAGCGGTGGAATGCGTAGATATATGGAAGAACACCAGTGGCGAAGGCGGCTCTCTGGTCTGCAACTGACGCTGAGGCTCGAAAGCATGGGTAGCGAACAGG'\n",
       "\\item 'TGGGGAATCTTAGACAATGGGCGCAAGCCTGATCTAGCCATGCCGCGTGATCGATGAAGGCCTTAGGGTTGTAAAGATCTTTCAGGTGGGAAGATAATGACGGTACCACCAGAAGAAGCCCCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGGGCTAGCGTTATTCGGAATTACTGGGCGTAAAGCGCACGTAGGCGGATCGGAAAGTCAGAGGTGAAATCCCAGGGCTCAACCCTGGAACTGCCTTTGAAACTCCCGATCTTGAGGTCGAGAGAGGTGAGTGGAATTCCGAGTGTAGAGGTGAAATTCGTAGATATTCGGAGGAACACCAGTGGCGAAGGCGGCTCACTGGCTCGATACTGACGCTGAGGTGCGAAAGCGTGGGGAGCAAACAGG'\n",
       "\\item 'TGGGGAATATTGGACAATGGGCGAAAGCCTGATCCAGCCATGCCGCGTGTGTGAAGAAGGTCTTCGGATTGTAAAGCACTTTAAGTTGGGAGGAAGGGCAGTAAGTTAATACCTTGCTGTTTTGACGTTACCAACAGAATAAGCACCGGCTAACTTCGTGCCAGCAGCCGCGGTAATACGAAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGCGCGTAGGTGGTTCAGCAAGTTGGATGTGAAATCCCCGGGCTCAACCTGGGAACTGCATCCAAAACTACTGAGCTAGAGTACGGTAGAGGGTGGTGGAATTTCCTGTGTAGCGGTGAAATGCGTAGATATAGGAAGGAACACCAGTGGCGAAGGCGACCACCTGGACTGATACTGACACTGAGGTGCGAAAGCGTGGGGAGCAAACAGG'\n",
       "\\item 'TGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCAACGCCGCGTGAGTGATGACGGTCTTCGGATTGTAAAGCTCTGTCTTCAGGGACGATAATGACGGTACCTGAGGAGGAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTACTGGGCGTAAAGGGAGCGTAGGTGGATATTTAAGTGGGATGTGAAATACTCGGGCTTAACCTGGGTGCTGCATTCCAAACTGGATATCTAGAGTGCAGGAGAGGAAAGTAGAATTCCTAGTGTAGCGGTGAAATGCGTAGAGATTAGGAAGAATACCAGTGGCGAAGGCGACTTTCTGGACTGTAACTGACACTGAGGCTCGAAAGCGTGGGGAGCAAACAGG'\n",
       "\\item 'TAGGGAATCTTCGGCAATGGACGGAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTTAGAGAAGAACGTTGGTAGGAGTGGAAAATCTACCAAGTGACGGTAACTAACCAGAAAGGGACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTCCCGAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGCGCAGGCGGTTCTTTAAGTCTGAAGTTAAAGGCAGTGGCTTAACCATTGTACGCTTTGGAAACTGGAGGACTTGAGTGCAGAAGGGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCGGTGGCGAAAGCGGCTCTCTGGTCTGTAACTGACGCTGAGGCTCGAAAGCGTGGGGAGCAAACAGG'\n",
       "\\item 'TAGGGAATATTGCTCAATGGGGGAAACCCTGAAGCAGCAACGCCGCGTGGAGGATGAAGGTTTTAGGATTGTAAACTCCTTTTGTTAGAGAAGATAATGACGGTATCTAACGAATAAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTACTCGGAATCACTGGGCGTAAAGAGCGCGTAGGCGGGATAGTCAGTCAGGTGTGAAATCCTATGGCTTAACCATAGAACTGCATTTGAAACTACTATTCTAGAGTGTGGGAGAGGTAGGTGGAATTCTTGGTGTAGGGGTAAAATCCGTAGAGATCAAGAGGAATACTCATTGCGAAGGCGACCTGCTGGAACATTACTGACGCTGATTGCGCGAAAGCGTGGGGAGCAAACAGG'\n",
       "\\item 'TGGGGAATTTTGGACAATGGGCGCAAGCCTGATCCAGCCATGCCGCGTGTCTGAAGAAGGCCTTCGGGTTGTAAAGGACTTTTGTCAGGGAAGAAAAGGCTGTTGCTAATATCAGCGGCTGATGACGGTACCTGAAGAATAAGCACCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGTGCGAGCGTTAATCGGAATTACTGGGCGTAAAGCGGGCGCAGACGGTTACTTAAGCAGGATGTGAAATCCCCGGGCTCAACCCGGGAACTGCGTTCTGAACTGGGTGACTCGAGTGTGTCAGAGGGAGGTAGAATTCCACGTGTAGCAGTGAAATGCGTAGAGATGTGGAGGAATACCGATGGCGAAGGCAGCCTCCTGGGACAACACTGACGTTCATGCCCGAAAGCGTGGGTAGCAAACAGG'\n",
       "\\item 'TTAGGAATCTTCCACAATGGGCGCAAGCCTGATGGAGCGACGCCGCGTGAGGGATGAAGGTTTTCGGATCGTAAACCTCTGAATCTGGGACGAAAGAGCCTTAGGGCAGATGACGGTACCAGAGTAATAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTACCCGGAATCACTGGGCGTAAAGGGCGTGTAGGCGGAAATTTAAGTCTGGTTTTAAAGACCGGGGCTCAACCTCGGGGATGGACTGGATACTGGATTTCTTGACCTCTGGAGAGGTAACTGGAATTCCTGGTGTAGCGGTGGAATGCGTAGATACCAGGAGGAACACCAATGGCGAAGGCAAGTTACTGGACAGAAGGTGACGCTGAGGCGCGAAAGTGTGGGGAGCAAACCGG'\n",
       "\\item 'TGGGGAATATTGGACAATGGGGGGAACCCTGATCCAGCCATGCCGCGTGTGTGAAGAAGGCCTTATGGTTGTAAAGCACTTTAAGCGAGGAGGAGGCTACTTTAGTTAATACCTAGAGATAGTGGACGTTACTCGCAGAATAAGCACCGGCTAACTCTGTGCCAGCAGCCGCGGTAATACAGAGGGTGCGAGCGTTAATCGGATTTACTGGGCGTAAAGCGTGCGTAGGCGGCTTATTAAGTCGGATGTGAAATCCCCGAGCTTAACTTGGGAATTGCATTCGATACTGGTGAGCTAGAGTATGGGAGAGGATGGTAGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGATGGCGAAGGCAGCCATCTGGCCTAATACTGACGCTGAGGTACGAAAGCATGGGGAGCAAACAGG'\n",
       "\\item 'TGAGGAATATTGGTCAATGGGCGAGAGCCTGAACCAGCCAAGTAGCGTGAAGGATGACTGCCCTATGGGTTGTAAACTTCTTTTATAAAGGAATAAAGTCGGGTATGGATACCCGTTTGCATGTACTTTATGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGAGCGTAGATGGATGTTTAAGTCAGTTGTGAAAGTTTGCGGCTCAACCGTAAAATTGCAGTTGATACTGGATATCTTGAGTGCAGTTGAGGCAGGCGGAATTCGTGGTGTAGCGGTGAAATGCTTAGATATCACGAAGAACTCCGATTGCGAAGGCAGCCTGCTAAGCTGCAACTGACATTGAGGCTCGAAAGTGTGGGTATCAAACAGG'\n",
       "\\item 'TAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGCCGCGTGAGTGATGAAGGCTTTCGGGTCGTAAAACTCTGTTGTTAGGGAAGAACAAGTGCTAGTTGAATAAGCTGGCACCTTGACGGTACCTAACCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGCGCGCAGGTGGTTTCTTAAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGGAGACTTGAGTGCAGAAGAGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGAGATATGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACACTGAGGCGCGAAAGCGTGGGGAGCAAACAGG'\n",
       "\\item 'TAGGGAATCTTCCGCAATGGGCGAAAGCCTGACGGAGCAACGCCGCGTGAGTGATGAAGGTCTTCGGATCGTAAAACTCTGTTATTAGGGAAGAACATATGTGTAAGTAACTGTGCACATCTTGACGGTACCTAATCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGCGCGTAGGCGGTTTTTTAAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGAAAACTTGAGTGCAGAAGAGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGCAGAGATATGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACGCTGATGTGCGAAAGCGTGGGGATCAAACAGG'\n",
       "\\item 'TAGGGAATCTTCCGCAATGGGCGAAAGCTTGACGGAGCAACGCCGCGTGAGTGATGAAGGTCTTCGGATCGTAAAACTCTGTTATTAGGGAAGAACAAATGTGTAAGTAACTATGCACGTCTTGACGGTACCTAATCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGCGCGTAGGCGGTTTTTTAAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGAAAACTTGAGTGCAGAAGAGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGCAGAGATATGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACGCTGATGTGCGAAAGCGTGGGGATCAAACAGG'\n",
       "\\item 'TAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGCCGCGTGTATGAAGAAGGTTTTCGGATCGTAAAGTACTGTTGTTAGAGAAGAACAAGGATAAGAGTAACTGCTTGTCCCTTGACGGTATCTAACCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGCGCGCAGGCGGTCTTTTAAGTCTGATGTGAAAGCCCCCGGCTTAACCGGGGAGGGTCATTGGAAACTGGAAGACTGGAGTGCAGAAGAGGAGAGTGGAATTCCACGTGTAGCGGTGAAATGCGTAGATATGTGGAGGAACACCAGTGGCGAAGGCGACTCTCTGGTCTGTAACTGACGCTGAGGCGCGAAAGCGTGGGGAGCAAACAGG'\n",
       "\\item 'TGGGGAATATTGCACAATGGGCGGAAGCCTGATGCAGCAACGCCGCGTGCGGGATGACGGCCTTCGGGTTGTAAACCGCTTTCGCCTGTGACGAAGCGTGAGTGACGGTAATGGGTAAAGAAGCACCGGCTAACTACGTGCCAGCAGCCGCGGTGATACGTAGGGTGCGAGCGTTGTCCGGATTTATTGGGCGTAAAGGGCTCGTAGGTGGTTGATCGCGTCGGAAGTGTAATCTTGGGGCTTAACCCTGAGCGTGCTTTCGATACGGGTTGACTTGAGGAAGGTAGGGGAGAATGGAATTCCTGGTGGAGCGGTGGAATGCGCAGATATCAGGAGGAACACCAGTGGCGAAGGCGGTTCTCTGGGCCTTTCCTGACGCTGAGGAGCGAAAGCGTGGGGAGCGAACAGGC'\n",
       "\\item 'TAGGGAATCTTCGGCAATGGACGAAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAACTCTGTTGTTAGAGAAGAACAAGGACGTTAGTAACTGAACGTCCCCTGACGGTATCTAACCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGCGCAGGCGGTTTCTTAAGTCTGATGTGAAAGCCCCCGGCTCAACCGGGGAGGGTCATTGGAAACTGGGAGACTTGAGTGCAGAAGAGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCAGTGGCGAAGGCGGCTCTCTGGTCTGTAACTGACGCTGAGGCTCGAAAGCGTGGGGAGCAAACAGG'\n",
       "\\item 'TGAGGAATATTGGTCAATGGGCGAGAGCCTGAACCAGCCAAGTAGCGTGAAGGATGACTGCCCTATGGGTTGTAAACTTCTTTTATAAAGGAATAAAGTCGGGTATGGATACCCGTTTGCATGTACTTTATGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGAGCGTAGATGGATATTTAAGTCAGTTGTGAAAGTTTGCGGCTCAACCGTAAAATTGCAGTTGATACTGGATATCTTGAGTGCAGTTGAGGCAGGCGGAATTCGTGGTGTAGCGGTGAAATGCTTAGATATCACGAAGAACTCCGATTGCGAAGGCAGCCTGCTAAGCTGCAACTGACATTGAGGCTCGAAAGTGTGGGTATCAAACAGG'\n",
       "\\item 'TGGGGAATATTGCACAATGGGCGAAAGCCTGATGCAGCGACGCCGCGTGAGGGATGGAGGCCTTCGGGTTGTAAACCTCTTTCGCTCATGGTCAAGCCGCAACTCAAGGTTGTGGTGAGGGTAGTGGGTAAAGAAGCGCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGCGCGAGCGTTGTCCGGAATTATTGGGCGTAAAGGGCTTGTAGGCGGTTGGTCGCGTCTGCCGTGAAATCCTCTGGCTTAACTGGGGGCGTGCGGTGGGTACGGGCTGACTTGAGTGCGGTAGGGGAGACTGGAACTCCTGGTGTAGCGGTGGAATGCGCAGATATCAGGAAGAACACCGGTGGCGAAGGCGGGTCTCTGGGCCGTTACTGACGCTGAGGAGCGAAAGCGTGGGGAGCGAACAGG'\n",
       "\\item 'TGAGGAATATTGGTCAATGGGCGCAGGCCTGAACCAGCCAAGTAGCGTGAAGGATGACTGCCCTATGGGTTGTAAACTTCTTTTATAAAGGAATAAAGTCGGGTATGGATACCCGTTTGCATGTACTTTATGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGAGCGTAGATGGATGTTTAAGTCAGTTGTGAAAGTTTGCGGCTCAACCGTAAAATTGCAGTTGATACTGGATATCTTGAGTGCAGTTGAGGCAGGCGGAATTCGTGGTGTAGCGGTGAAATGCTTAGATATCACGAAGAACTCCGATTGCGAAGGCAGCCTGCTAAGCTGCAACTGACATTGAGGCTCGAAAGTGTGGGTATCAAACAGG'\n",
       "\\item 'TGAGGAATATTGGTCAATGGGCGAGAGCCTGAACCAGCCAAGTAGCGTGAAGGATGACTGCCCTATGGGTTGTAAACTTCTTTTATAAAGGAATAAAGTCGGGTATGCATACCCGTTTGCATGTACTTTATGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGAGCGTAGATGGATGTTTAAGTCAGTTGTGAAAGTTTGCGGCTCAACCGTAAAATTGCAGTTGATACTGGATATCTTGAGTGCAGTTGAGGCAGGCGGAATTCGTGGTGTAGCGGTGAAATGCTTAGATATCACGAGGAACTCCGATTGCGAAGGCAGCCTGCTAAGCTGCAACTGACATTGAGGCTCGAAAGTGTGGGTATCAAACAGG'\n",
       "\\item 'TAGGGAATCTTCGGCAATGGACGGAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTAAGAGAAGAACGAGTGTGAGAGTGGAAAGTTCACACTGTGACGGTATCTTACCAGAAAGGGACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTCCCGAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGCGCAGGCGGTTAGATAAGTCTGAAGTTAAAGGCTGTGGCTTAACCATAGTAGGCTTTGGAAACTGTTTAACTTGAGTGCAAGAGGGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCGGTGGCGAAAGCGGCTCTCTGGCTTGTAACTGACGCTGAGGCTCGAAAGCGTGGGGAGCAAACAGG'\n",
       "\\item 'TGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCAACGCCGCGTGAGTGATGACGGTCTTCGGATTGTAAAGCTCTGTCTTCAGGGACGATAATGACGGTACCTGAGGAGGAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTACTGGGCGTAAAGGGAGCGTAGGTGGATATTTAAGTGGGATGTGAAATACTCGGGCTTAACCTGGGTGCTGCATTCCAAACTGGATATCTAGAGTGCAGGAGAGGAAAGTAGAATTCTTAGTGTAGCGGTGAAATGCGTAGAGATTAGGAAGAATACCAGTGGCGAAGGCGACTTTCTGGACTGTAACTGACACTGAGGCTCGAAAGCGTGGGGAGCAAACAGG'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'TAGGGAATCTTCGGCAATGGACGAAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTAAGTCAAGAACGTGTGTGAGAGTGGAAAGTTCACACAGTGACGGTAGCTTACCAGAAAGGGACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTCCCGAGCGTTGTCCGGATTTATTGGGCGTAAAGGGAGCGCAGGCGGTCAGGAAAGTCTGGAGTAAAAGGCTATGGCTCAACCATAGTGTGCTCTGGAAACTGTCTGACTTGAGTGCAGAAGGGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCAGTGGCGAAAGCGGCTCTCTGGTCTGTCACTGACGCTGAGGCTCGAAAGCGTGGGTAGCGAACAGG'\n",
       "2. 'TGGGGAATATTGCACAATGGGCGCAAGCCTGATGCAGCCATGCCGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAAGGGAGTAAAGTTAATACCTTTGCTCATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGCACGCAGGCGGTTTGTTAAGTCAGATGTGAAATCCCCGGGCTCAACCTGGGAACTGCATCTGATACTGGCAAGCTTGAGTCTCGTAGAGGGGGGTAGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCGAAGGCGGCCCCCTGGACGAAGACTGACGCTCAGGTGCGAAAGCGTGGGGAGCAAACAGG'\n",
       "3. 'TAGGGAATCTTCCGCAATGGGCGAAAGCCTGACGGAGCAACGCCGCGTGAGTGATGAAGGTCTTCGGATCGTAAAACTCTGTTATTAGGGAAGAACAAATGTGTAAGTAACTATGCACGTCTTGACGGTACCTAATCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGCGCGTAGGCGGTTTTTTAAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGAAAACTTGAGTGCAGAAGAGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGCAGAGATATGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACGCTGATGTGCGAAAGCGTGGGGATCAAACAGG'\n",
       "4. 'TAGGGAATCTTCCACAATGGACGCAAGTCTGATGGAGCAACGCCGCGTGAGTGAAGAAGGGTTTCGGCTCGTAAAGCTCTGTTGGTAGTGAAGAAAGATAGAGGTAGTAACTGGCCTTTATTTGACGGTAATTACTTAGAAAGTCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGTGCAGGCGGTTCAATAAGTCTGATGTGAAAGCCTTCGGCTCAACCGGAGAATTGCATCAGAAACTGTTGAACTTGAGTGCAGAAGAGGAGAGTGGAACTCCATGTGTAGCGGTGGAATGCGTAGATATATGGAAGAACACCAGTGGCGAAGGCGGCTCTCTGGTCTGCAACTGACGCTGAGGCTCGAAAGCATGGGTAGCGAACAGG'\n",
       "5. 'TGGGGAATCTTAGACAATGGGCGCAAGCCTGATCTAGCCATGCCGCGTGATCGATGAAGGCCTTAGGGTTGTAAAGATCTTTCAGGTGGGAAGATAATGACGGTACCACCAGAAGAAGCCCCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGGGCTAGCGTTATTCGGAATTACTGGGCGTAAAGCGCACGTAGGCGGATCGGAAAGTCAGAGGTGAAATCCCAGGGCTCAACCCTGGAACTGCCTTTGAAACTCCCGATCTTGAGGTCGAGAGAGGTGAGTGGAATTCCGAGTGTAGAGGTGAAATTCGTAGATATTCGGAGGAACACCAGTGGCGAAGGCGGCTCACTGGCTCGATACTGACGCTGAGGTGCGAAAGCGTGGGGAGCAAACAGG'\n",
       "6. 'TGGGGAATATTGGACAATGGGCGAAAGCCTGATCCAGCCATGCCGCGTGTGTGAAGAAGGTCTTCGGATTGTAAAGCACTTTAAGTTGGGAGGAAGGGCAGTAAGTTAATACCTTGCTGTTTTGACGTTACCAACAGAATAAGCACCGGCTAACTTCGTGCCAGCAGCCGCGGTAATACGAAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGCGCGTAGGTGGTTCAGCAAGTTGGATGTGAAATCCCCGGGCTCAACCTGGGAACTGCATCCAAAACTACTGAGCTAGAGTACGGTAGAGGGTGGTGGAATTTCCTGTGTAGCGGTGAAATGCGTAGATATAGGAAGGAACACCAGTGGCGAAGGCGACCACCTGGACTGATACTGACACTGAGGTGCGAAAGCGTGGGGAGCAAACAGG'\n",
       "7. 'TGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCAACGCCGCGTGAGTGATGACGGTCTTCGGATTGTAAAGCTCTGTCTTCAGGGACGATAATGACGGTACCTGAGGAGGAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTACTGGGCGTAAAGGGAGCGTAGGTGGATATTTAAGTGGGATGTGAAATACTCGGGCTTAACCTGGGTGCTGCATTCCAAACTGGATATCTAGAGTGCAGGAGAGGAAAGTAGAATTCCTAGTGTAGCGGTGAAATGCGTAGAGATTAGGAAGAATACCAGTGGCGAAGGCGACTTTCTGGACTGTAACTGACACTGAGGCTCGAAAGCGTGGGGAGCAAACAGG'\n",
       "8. 'TAGGGAATCTTCGGCAATGGACGGAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTTAGAGAAGAACGTTGGTAGGAGTGGAAAATCTACCAAGTGACGGTAACTAACCAGAAAGGGACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTCCCGAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGCGCAGGCGGTTCTTTAAGTCTGAAGTTAAAGGCAGTGGCTTAACCATTGTACGCTTTGGAAACTGGAGGACTTGAGTGCAGAAGGGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCGGTGGCGAAAGCGGCTCTCTGGTCTGTAACTGACGCTGAGGCTCGAAAGCGTGGGGAGCAAACAGG'\n",
       "9. 'TAGGGAATATTGCTCAATGGGGGAAACCCTGAAGCAGCAACGCCGCGTGGAGGATGAAGGTTTTAGGATTGTAAACTCCTTTTGTTAGAGAAGATAATGACGGTATCTAACGAATAAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTACTCGGAATCACTGGGCGTAAAGAGCGCGTAGGCGGGATAGTCAGTCAGGTGTGAAATCCTATGGCTTAACCATAGAACTGCATTTGAAACTACTATTCTAGAGTGTGGGAGAGGTAGGTGGAATTCTTGGTGTAGGGGTAAAATCCGTAGAGATCAAGAGGAATACTCATTGCGAAGGCGACCTGCTGGAACATTACTGACGCTGATTGCGCGAAAGCGTGGGGAGCAAACAGG'\n",
       "10. 'TGGGGAATTTTGGACAATGGGCGCAAGCCTGATCCAGCCATGCCGCGTGTCTGAAGAAGGCCTTCGGGTTGTAAAGGACTTTTGTCAGGGAAGAAAAGGCTGTTGCTAATATCAGCGGCTGATGACGGTACCTGAAGAATAAGCACCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGTGCGAGCGTTAATCGGAATTACTGGGCGTAAAGCGGGCGCAGACGGTTACTTAAGCAGGATGTGAAATCCCCGGGCTCAACCCGGGAACTGCGTTCTGAACTGGGTGACTCGAGTGTGTCAGAGGGAGGTAGAATTCCACGTGTAGCAGTGAAATGCGTAGAGATGTGGAGGAATACCGATGGCGAAGGCAGCCTCCTGGGACAACACTGACGTTCATGCCCGAAAGCGTGGGTAGCAAACAGG'\n",
       "11. 'TTAGGAATCTTCCACAATGGGCGCAAGCCTGATGGAGCGACGCCGCGTGAGGGATGAAGGTTTTCGGATCGTAAACCTCTGAATCTGGGACGAAAGAGCCTTAGGGCAGATGACGGTACCAGAGTAATAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTACCCGGAATCACTGGGCGTAAAGGGCGTGTAGGCGGAAATTTAAGTCTGGTTTTAAAGACCGGGGCTCAACCTCGGGGATGGACTGGATACTGGATTTCTTGACCTCTGGAGAGGTAACTGGAATTCCTGGTGTAGCGGTGGAATGCGTAGATACCAGGAGGAACACCAATGGCGAAGGCAAGTTACTGGACAGAAGGTGACGCTGAGGCGCGAAAGTGTGGGGAGCAAACCGG'\n",
       "12. 'TGGGGAATATTGGACAATGGGGGGAACCCTGATCCAGCCATGCCGCGTGTGTGAAGAAGGCCTTATGGTTGTAAAGCACTTTAAGCGAGGAGGAGGCTACTTTAGTTAATACCTAGAGATAGTGGACGTTACTCGCAGAATAAGCACCGGCTAACTCTGTGCCAGCAGCCGCGGTAATACAGAGGGTGCGAGCGTTAATCGGATTTACTGGGCGTAAAGCGTGCGTAGGCGGCTTATTAAGTCGGATGTGAAATCCCCGAGCTTAACTTGGGAATTGCATTCGATACTGGTGAGCTAGAGTATGGGAGAGGATGGTAGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGATGGCGAAGGCAGCCATCTGGCCTAATACTGACGCTGAGGTACGAAAGCATGGGGAGCAAACAGG'\n",
       "13. 'TGAGGAATATTGGTCAATGGGCGAGAGCCTGAACCAGCCAAGTAGCGTGAAGGATGACTGCCCTATGGGTTGTAAACTTCTTTTATAAAGGAATAAAGTCGGGTATGGATACCCGTTTGCATGTACTTTATGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGAGCGTAGATGGATGTTTAAGTCAGTTGTGAAAGTTTGCGGCTCAACCGTAAAATTGCAGTTGATACTGGATATCTTGAGTGCAGTTGAGGCAGGCGGAATTCGTGGTGTAGCGGTGAAATGCTTAGATATCACGAAGAACTCCGATTGCGAAGGCAGCCTGCTAAGCTGCAACTGACATTGAGGCTCGAAAGTGTGGGTATCAAACAGG'\n",
       "14. 'TAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGCCGCGTGAGTGATGAAGGCTTTCGGGTCGTAAAACTCTGTTGTTAGGGAAGAACAAGTGCTAGTTGAATAAGCTGGCACCTTGACGGTACCTAACCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGCGCGCAGGTGGTTTCTTAAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGGAGACTTGAGTGCAGAAGAGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGAGATATGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACACTGAGGCGCGAAAGCGTGGGGAGCAAACAGG'\n",
       "15. 'TAGGGAATCTTCCGCAATGGGCGAAAGCCTGACGGAGCAACGCCGCGTGAGTGATGAAGGTCTTCGGATCGTAAAACTCTGTTATTAGGGAAGAACATATGTGTAAGTAACTGTGCACATCTTGACGGTACCTAATCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGCGCGTAGGCGGTTTTTTAAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGAAAACTTGAGTGCAGAAGAGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGCAGAGATATGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACGCTGATGTGCGAAAGCGTGGGGATCAAACAGG'\n",
       "16. 'TAGGGAATCTTCCGCAATGGGCGAAAGCTTGACGGAGCAACGCCGCGTGAGTGATGAAGGTCTTCGGATCGTAAAACTCTGTTATTAGGGAAGAACAAATGTGTAAGTAACTATGCACGTCTTGACGGTACCTAATCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGCGCGTAGGCGGTTTTTTAAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGAAAACTTGAGTGCAGAAGAGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGCAGAGATATGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACGCTGATGTGCGAAAGCGTGGGGATCAAACAGG'\n",
       "17. 'TAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGCCGCGTGTATGAAGAAGGTTTTCGGATCGTAAAGTACTGTTGTTAGAGAAGAACAAGGATAAGAGTAACTGCTTGTCCCTTGACGGTATCTAACCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGCGCGCAGGCGGTCTTTTAAGTCTGATGTGAAAGCCCCCGGCTTAACCGGGGAGGGTCATTGGAAACTGGAAGACTGGAGTGCAGAAGAGGAGAGTGGAATTCCACGTGTAGCGGTGAAATGCGTAGATATGTGGAGGAACACCAGTGGCGAAGGCGACTCTCTGGTCTGTAACTGACGCTGAGGCGCGAAAGCGTGGGGAGCAAACAGG'\n",
       "18. 'TGGGGAATATTGCACAATGGGCGGAAGCCTGATGCAGCAACGCCGCGTGCGGGATGACGGCCTTCGGGTTGTAAACCGCTTTCGCCTGTGACGAAGCGTGAGTGACGGTAATGGGTAAAGAAGCACCGGCTAACTACGTGCCAGCAGCCGCGGTGATACGTAGGGTGCGAGCGTTGTCCGGATTTATTGGGCGTAAAGGGCTCGTAGGTGGTTGATCGCGTCGGAAGTGTAATCTTGGGGCTTAACCCTGAGCGTGCTTTCGATACGGGTTGACTTGAGGAAGGTAGGGGAGAATGGAATTCCTGGTGGAGCGGTGGAATGCGCAGATATCAGGAGGAACACCAGTGGCGAAGGCGGTTCTCTGGGCCTTTCCTGACGCTGAGGAGCGAAAGCGTGGGGAGCGAACAGGC'\n",
       "19. 'TAGGGAATCTTCGGCAATGGACGAAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAACTCTGTTGTTAGAGAAGAACAAGGACGTTAGTAACTGAACGTCCCCTGACGGTATCTAACCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGCGCAGGCGGTTTCTTAAGTCTGATGTGAAAGCCCCCGGCTCAACCGGGGAGGGTCATTGGAAACTGGGAGACTTGAGTGCAGAAGAGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCAGTGGCGAAGGCGGCTCTCTGGTCTGTAACTGACGCTGAGGCTCGAAAGCGTGGGGAGCAAACAGG'\n",
       "20. 'TGAGGAATATTGGTCAATGGGCGAGAGCCTGAACCAGCCAAGTAGCGTGAAGGATGACTGCCCTATGGGTTGTAAACTTCTTTTATAAAGGAATAAAGTCGGGTATGGATACCCGTTTGCATGTACTTTATGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGAGCGTAGATGGATATTTAAGTCAGTTGTGAAAGTTTGCGGCTCAACCGTAAAATTGCAGTTGATACTGGATATCTTGAGTGCAGTTGAGGCAGGCGGAATTCGTGGTGTAGCGGTGAAATGCTTAGATATCACGAAGAACTCCGATTGCGAAGGCAGCCTGCTAAGCTGCAACTGACATTGAGGCTCGAAAGTGTGGGTATCAAACAGG'\n",
       "21. 'TGGGGAATATTGCACAATGGGCGAAAGCCTGATGCAGCGACGCCGCGTGAGGGATGGAGGCCTTCGGGTTGTAAACCTCTTTCGCTCATGGTCAAGCCGCAACTCAAGGTTGTGGTGAGGGTAGTGGGTAAAGAAGCGCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGCGCGAGCGTTGTCCGGAATTATTGGGCGTAAAGGGCTTGTAGGCGGTTGGTCGCGTCTGCCGTGAAATCCTCTGGCTTAACTGGGGGCGTGCGGTGGGTACGGGCTGACTTGAGTGCGGTAGGGGAGACTGGAACTCCTGGTGTAGCGGTGGAATGCGCAGATATCAGGAAGAACACCGGTGGCGAAGGCGGGTCTCTGGGCCGTTACTGACGCTGAGGAGCGAAAGCGTGGGGAGCGAACAGG'\n",
       "22. 'TGAGGAATATTGGTCAATGGGCGCAGGCCTGAACCAGCCAAGTAGCGTGAAGGATGACTGCCCTATGGGTTGTAAACTTCTTTTATAAAGGAATAAAGTCGGGTATGGATACCCGTTTGCATGTACTTTATGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGAGCGTAGATGGATGTTTAAGTCAGTTGTGAAAGTTTGCGGCTCAACCGTAAAATTGCAGTTGATACTGGATATCTTGAGTGCAGTTGAGGCAGGCGGAATTCGTGGTGTAGCGGTGAAATGCTTAGATATCACGAAGAACTCCGATTGCGAAGGCAGCCTGCTAAGCTGCAACTGACATTGAGGCTCGAAAGTGTGGGTATCAAACAGG'\n",
       "23. 'TGAGGAATATTGGTCAATGGGCGAGAGCCTGAACCAGCCAAGTAGCGTGAAGGATGACTGCCCTATGGGTTGTAAACTTCTTTTATAAAGGAATAAAGTCGGGTATGCATACCCGTTTGCATGTACTTTATGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGAGCGTAGATGGATGTTTAAGTCAGTTGTGAAAGTTTGCGGCTCAACCGTAAAATTGCAGTTGATACTGGATATCTTGAGTGCAGTTGAGGCAGGCGGAATTCGTGGTGTAGCGGTGAAATGCTTAGATATCACGAGGAACTCCGATTGCGAAGGCAGCCTGCTAAGCTGCAACTGACATTGAGGCTCGAAAGTGTGGGTATCAAACAGG'\n",
       "24. 'TAGGGAATCTTCGGCAATGGACGGAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTAAGAGAAGAACGAGTGTGAGAGTGGAAAGTTCACACTGTGACGGTATCTTACCAGAAAGGGACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTCCCGAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGCGCAGGCGGTTAGATAAGTCTGAAGTTAAAGGCTGTGGCTTAACCATAGTAGGCTTTGGAAACTGTTTAACTTGAGTGCAAGAGGGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCGGTGGCGAAAGCGGCTCTCTGGCTTGTAACTGACGCTGAGGCTCGAAAGCGTGGGGAGCAAACAGG'\n",
       "25. 'TGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCAACGCCGCGTGAGTGATGACGGTCTTCGGATTGTAAAGCTCTGTCTTCAGGGACGATAATGACGGTACCTGAGGAGGAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTACTGGGCGTAAAGGGAGCGTAGGTGGATATTTAAGTGGGATGTGAAATACTCGGGCTTAACCTGGGTGCTGCATTCCAAACTGGATATCTAGAGTGCAGGAGAGGAAAGTAGAATTCTTAGTGTAGCGGTGAAATGCGTAGAGATTAGGAAGAATACCAGTGGCGAAGGCGACTTTCTGGACTGTAACTGACACTGAGGCTCGAAAGCGTGGGGAGCAAACAGG'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"TAGGGAATCTTCGGCAATGGACGAAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTAAGTCAAGAACGTGTGTGAGAGTGGAAAGTTCACACAGTGACGGTAGCTTACCAGAAAGGGACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTCCCGAGCGTTGTCCGGATTTATTGGGCGTAAAGGGAGCGCAGGCGGTCAGGAAAGTCTGGAGTAAAAGGCTATGGCTCAACCATAGTGTGCTCTGGAAACTGTCTGACTTGAGTGCAGAAGGGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCAGTGGCGAAAGCGGCTCTCTGGTCTGTCACTGACGCTGAGGCTCGAAAGCGTGGGTAGCGAACAGG\" \n",
       " [2] \"TGGGGAATATTGCACAATGGGCGCAAGCCTGATGCAGCCATGCCGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAAGGGAGTAAAGTTAATACCTTTGCTCATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGCACGCAGGCGGTTTGTTAAGTCAGATGTGAAATCCCCGGGCTCAACCTGGGAACTGCATCTGATACTGGCAAGCTTGAGTCTCGTAGAGGGGGGTAGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCGAAGGCGGCCCCCTGGACGAAGACTGACGCTCAGGTGCGAAAGCGTGGGGAGCAAACAGG\" \n",
       " [3] \"TAGGGAATCTTCCGCAATGGGCGAAAGCCTGACGGAGCAACGCCGCGTGAGTGATGAAGGTCTTCGGATCGTAAAACTCTGTTATTAGGGAAGAACAAATGTGTAAGTAACTATGCACGTCTTGACGGTACCTAATCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGCGCGTAGGCGGTTTTTTAAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGAAAACTTGAGTGCAGAAGAGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGCAGAGATATGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACGCTGATGTGCGAAAGCGTGGGGATCAAACAGG\" \n",
       " [4] \"TAGGGAATCTTCCACAATGGACGCAAGTCTGATGGAGCAACGCCGCGTGAGTGAAGAAGGGTTTCGGCTCGTAAAGCTCTGTTGGTAGTGAAGAAAGATAGAGGTAGTAACTGGCCTTTATTTGACGGTAATTACTTAGAAAGTCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGTGCAGGCGGTTCAATAAGTCTGATGTGAAAGCCTTCGGCTCAACCGGAGAATTGCATCAGAAACTGTTGAACTTGAGTGCAGAAGAGGAGAGTGGAACTCCATGTGTAGCGGTGGAATGCGTAGATATATGGAAGAACACCAGTGGCGAAGGCGGCTCTCTGGTCTGCAACTGACGCTGAGGCTCGAAAGCATGGGTAGCGAACAGG\" \n",
       " [5] \"TGGGGAATCTTAGACAATGGGCGCAAGCCTGATCTAGCCATGCCGCGTGATCGATGAAGGCCTTAGGGTTGTAAAGATCTTTCAGGTGGGAAGATAATGACGGTACCACCAGAAGAAGCCCCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGGGCTAGCGTTATTCGGAATTACTGGGCGTAAAGCGCACGTAGGCGGATCGGAAAGTCAGAGGTGAAATCCCAGGGCTCAACCCTGGAACTGCCTTTGAAACTCCCGATCTTGAGGTCGAGAGAGGTGAGTGGAATTCCGAGTGTAGAGGTGAAATTCGTAGATATTCGGAGGAACACCAGTGGCGAAGGCGGCTCACTGGCTCGATACTGACGCTGAGGTGCGAAAGCGTGGGGAGCAAACAGG\"                          \n",
       " [6] \"TGGGGAATATTGGACAATGGGCGAAAGCCTGATCCAGCCATGCCGCGTGTGTGAAGAAGGTCTTCGGATTGTAAAGCACTTTAAGTTGGGAGGAAGGGCAGTAAGTTAATACCTTGCTGTTTTGACGTTACCAACAGAATAAGCACCGGCTAACTTCGTGCCAGCAGCCGCGGTAATACGAAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGCGCGTAGGTGGTTCAGCAAGTTGGATGTGAAATCCCCGGGCTCAACCTGGGAACTGCATCCAAAACTACTGAGCTAGAGTACGGTAGAGGGTGGTGGAATTTCCTGTGTAGCGGTGAAATGCGTAGATATAGGAAGGAACACCAGTGGCGAAGGCGACCACCTGGACTGATACTGACACTGAGGTGCGAAAGCGTGGGGAGCAAACAGG\" \n",
       " [7] \"TGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCAACGCCGCGTGAGTGATGACGGTCTTCGGATTGTAAAGCTCTGTCTTCAGGGACGATAATGACGGTACCTGAGGAGGAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTACTGGGCGTAAAGGGAGCGTAGGTGGATATTTAAGTGGGATGTGAAATACTCGGGCTTAACCTGGGTGCTGCATTCCAAACTGGATATCTAGAGTGCAGGAGAGGAAAGTAGAATTCCTAGTGTAGCGGTGAAATGCGTAGAGATTAGGAAGAATACCAGTGGCGAAGGCGACTTTCTGGACTGTAACTGACACTGAGGCTCGAAAGCGTGGGGAGCAAACAGG\"                          \n",
       " [8] \"TAGGGAATCTTCGGCAATGGACGGAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTTAGAGAAGAACGTTGGTAGGAGTGGAAAATCTACCAAGTGACGGTAACTAACCAGAAAGGGACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTCCCGAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGCGCAGGCGGTTCTTTAAGTCTGAAGTTAAAGGCAGTGGCTTAACCATTGTACGCTTTGGAAACTGGAGGACTTGAGTGCAGAAGGGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCGGTGGCGAAAGCGGCTCTCTGGTCTGTAACTGACGCTGAGGCTCGAAAGCGTGGGGAGCAAACAGG\" \n",
       " [9] \"TAGGGAATATTGCTCAATGGGGGAAACCCTGAAGCAGCAACGCCGCGTGGAGGATGAAGGTTTTAGGATTGTAAACTCCTTTTGTTAGAGAAGATAATGACGGTATCTAACGAATAAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTACTCGGAATCACTGGGCGTAAAGAGCGCGTAGGCGGGATAGTCAGTCAGGTGTGAAATCCTATGGCTTAACCATAGAACTGCATTTGAAACTACTATTCTAGAGTGTGGGAGAGGTAGGTGGAATTCTTGGTGTAGGGGTAAAATCCGTAGAGATCAAGAGGAATACTCATTGCGAAGGCGACCTGCTGGAACATTACTGACGCTGATTGCGCGAAAGCGTGGGGAGCAAACAGG\"                         \n",
       "[10] \"TGGGGAATTTTGGACAATGGGCGCAAGCCTGATCCAGCCATGCCGCGTGTCTGAAGAAGGCCTTCGGGTTGTAAAGGACTTTTGTCAGGGAAGAAAAGGCTGTTGCTAATATCAGCGGCTGATGACGGTACCTGAAGAATAAGCACCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGTGCGAGCGTTAATCGGAATTACTGGGCGTAAAGCGGGCGCAGACGGTTACTTAAGCAGGATGTGAAATCCCCGGGCTCAACCCGGGAACTGCGTTCTGAACTGGGTGACTCGAGTGTGTCAGAGGGAGGTAGAATTCCACGTGTAGCAGTGAAATGCGTAGAGATGTGGAGGAATACCGATGGCGAAGGCAGCCTCCTGGGACAACACTGACGTTCATGCCCGAAAGCGTGGGTAGCAAACAGG\" \n",
       "[11] \"TTAGGAATCTTCCACAATGGGCGCAAGCCTGATGGAGCGACGCCGCGTGAGGGATGAAGGTTTTCGGATCGTAAACCTCTGAATCTGGGACGAAAGAGCCTTAGGGCAGATGACGGTACCAGAGTAATAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTACCCGGAATCACTGGGCGTAAAGGGCGTGTAGGCGGAAATTTAAGTCTGGTTTTAAAGACCGGGGCTCAACCTCGGGGATGGACTGGATACTGGATTTCTTGACCTCTGGAGAGGTAACTGGAATTCCTGGTGTAGCGGTGGAATGCGTAGATACCAGGAGGAACACCAATGGCGAAGGCAAGTTACTGGACAGAAGGTGACGCTGAGGCGCGAAAGTGTGGGGAGCAAACCGG\"              \n",
       "[12] \"TGGGGAATATTGGACAATGGGGGGAACCCTGATCCAGCCATGCCGCGTGTGTGAAGAAGGCCTTATGGTTGTAAAGCACTTTAAGCGAGGAGGAGGCTACTTTAGTTAATACCTAGAGATAGTGGACGTTACTCGCAGAATAAGCACCGGCTAACTCTGTGCCAGCAGCCGCGGTAATACAGAGGGTGCGAGCGTTAATCGGATTTACTGGGCGTAAAGCGTGCGTAGGCGGCTTATTAAGTCGGATGTGAAATCCCCGAGCTTAACTTGGGAATTGCATTCGATACTGGTGAGCTAGAGTATGGGAGAGGATGGTAGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGATGGCGAAGGCAGCCATCTGGCCTAATACTGACGCTGAGGTACGAAAGCATGGGGAGCAAACAGG\"\n",
       "[13] \"TGAGGAATATTGGTCAATGGGCGAGAGCCTGAACCAGCCAAGTAGCGTGAAGGATGACTGCCCTATGGGTTGTAAACTTCTTTTATAAAGGAATAAAGTCGGGTATGGATACCCGTTTGCATGTACTTTATGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGAGCGTAGATGGATGTTTAAGTCAGTTGTGAAAGTTTGCGGCTCAACCGTAAAATTGCAGTTGATACTGGATATCTTGAGTGCAGTTGAGGCAGGCGGAATTCGTGGTGTAGCGGTGAAATGCTTAGATATCACGAAGAACTCCGATTGCGAAGGCAGCCTGCTAAGCTGCAACTGACATTGAGGCTCGAAAGTGTGGGTATCAAACAGG\"      \n",
       "[14] \"TAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGCCGCGTGAGTGATGAAGGCTTTCGGGTCGTAAAACTCTGTTGTTAGGGAAGAACAAGTGCTAGTTGAATAAGCTGGCACCTTGACGGTACCTAACCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGCGCGCAGGTGGTTTCTTAAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGGAGACTTGAGTGCAGAAGAGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGAGATATGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACACTGAGGCGCGAAAGCGTGGGGAGCAAACAGG\"\n",
       "[15] \"TAGGGAATCTTCCGCAATGGGCGAAAGCCTGACGGAGCAACGCCGCGTGAGTGATGAAGGTCTTCGGATCGTAAAACTCTGTTATTAGGGAAGAACATATGTGTAAGTAACTGTGCACATCTTGACGGTACCTAATCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGCGCGTAGGCGGTTTTTTAAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGAAAACTTGAGTGCAGAAGAGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGCAGAGATATGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACGCTGATGTGCGAAAGCGTGGGGATCAAACAGG\" \n",
       "[16] \"TAGGGAATCTTCCGCAATGGGCGAAAGCTTGACGGAGCAACGCCGCGTGAGTGATGAAGGTCTTCGGATCGTAAAACTCTGTTATTAGGGAAGAACAAATGTGTAAGTAACTATGCACGTCTTGACGGTACCTAATCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGCGCGTAGGCGGTTTTTTAAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGAAAACTTGAGTGCAGAAGAGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGCAGAGATATGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACGCTGATGTGCGAAAGCGTGGGGATCAAACAGG\" \n",
       "[17] \"TAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGCCGCGTGTATGAAGAAGGTTTTCGGATCGTAAAGTACTGTTGTTAGAGAAGAACAAGGATAAGAGTAACTGCTTGTCCCTTGACGGTATCTAACCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGCGCGCAGGCGGTCTTTTAAGTCTGATGTGAAAGCCCCCGGCTTAACCGGGGAGGGTCATTGGAAACTGGAAGACTGGAGTGCAGAAGAGGAGAGTGGAATTCCACGTGTAGCGGTGAAATGCGTAGATATGTGGAGGAACACCAGTGGCGAAGGCGACTCTCTGGTCTGTAACTGACGCTGAGGCGCGAAAGCGTGGGGAGCAAACAGG\" \n",
       "[18] \"TGGGGAATATTGCACAATGGGCGGAAGCCTGATGCAGCAACGCCGCGTGCGGGATGACGGCCTTCGGGTTGTAAACCGCTTTCGCCTGTGACGAAGCGTGAGTGACGGTAATGGGTAAAGAAGCACCGGCTAACTACGTGCCAGCAGCCGCGGTGATACGTAGGGTGCGAGCGTTGTCCGGATTTATTGGGCGTAAAGGGCTCGTAGGTGGTTGATCGCGTCGGAAGTGTAATCTTGGGGCTTAACCCTGAGCGTGCTTTCGATACGGGTTGACTTGAGGAAGGTAGGGGAGAATGGAATTCCTGGTGGAGCGGTGGAATGCGCAGATATCAGGAGGAACACCAGTGGCGAAGGCGGTTCTCTGGGCCTTTCCTGACGCTGAGGAGCGAAAGCGTGGGGAGCGAACAGGC\"                    \n",
       "[19] \"TAGGGAATCTTCGGCAATGGACGAAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAACTCTGTTGTTAGAGAAGAACAAGGACGTTAGTAACTGAACGTCCCCTGACGGTATCTAACCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGCGCAGGCGGTTTCTTAAGTCTGATGTGAAAGCCCCCGGCTCAACCGGGGAGGGTCATTGGAAACTGGGAGACTTGAGTGCAGAAGAGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCAGTGGCGAAGGCGGCTCTCTGGTCTGTAACTGACGCTGAGGCTCGAAAGCGTGGGGAGCAAACAGG\" \n",
       "[20] \"TGAGGAATATTGGTCAATGGGCGAGAGCCTGAACCAGCCAAGTAGCGTGAAGGATGACTGCCCTATGGGTTGTAAACTTCTTTTATAAAGGAATAAAGTCGGGTATGGATACCCGTTTGCATGTACTTTATGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGAGCGTAGATGGATATTTAAGTCAGTTGTGAAAGTTTGCGGCTCAACCGTAAAATTGCAGTTGATACTGGATATCTTGAGTGCAGTTGAGGCAGGCGGAATTCGTGGTGTAGCGGTGAAATGCTTAGATATCACGAAGAACTCCGATTGCGAAGGCAGCCTGCTAAGCTGCAACTGACATTGAGGCTCGAAAGTGTGGGTATCAAACAGG\"      \n",
       "[21] \"TGGGGAATATTGCACAATGGGCGAAAGCCTGATGCAGCGACGCCGCGTGAGGGATGGAGGCCTTCGGGTTGTAAACCTCTTTCGCTCATGGTCAAGCCGCAACTCAAGGTTGTGGTGAGGGTAGTGGGTAAAGAAGCGCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGCGCGAGCGTTGTCCGGAATTATTGGGCGTAAAGGGCTTGTAGGCGGTTGGTCGCGTCTGCCGTGAAATCCTCTGGCTTAACTGGGGGCGTGCGGTGGGTACGGGCTGACTTGAGTGCGGTAGGGGAGACTGGAACTCCTGGTGTAGCGGTGGAATGCGCAGATATCAGGAAGAACACCGGTGGCGAAGGCGGGTCTCTGGGCCGTTACTGACGCTGAGGAGCGAAAGCGTGGGGAGCGAACAGG\"        \n",
       "[22] \"TGAGGAATATTGGTCAATGGGCGCAGGCCTGAACCAGCCAAGTAGCGTGAAGGATGACTGCCCTATGGGTTGTAAACTTCTTTTATAAAGGAATAAAGTCGGGTATGGATACCCGTTTGCATGTACTTTATGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGAGCGTAGATGGATGTTTAAGTCAGTTGTGAAAGTTTGCGGCTCAACCGTAAAATTGCAGTTGATACTGGATATCTTGAGTGCAGTTGAGGCAGGCGGAATTCGTGGTGTAGCGGTGAAATGCTTAGATATCACGAAGAACTCCGATTGCGAAGGCAGCCTGCTAAGCTGCAACTGACATTGAGGCTCGAAAGTGTGGGTATCAAACAGG\"      \n",
       "[23] \"TGAGGAATATTGGTCAATGGGCGAGAGCCTGAACCAGCCAAGTAGCGTGAAGGATGACTGCCCTATGGGTTGTAAACTTCTTTTATAAAGGAATAAAGTCGGGTATGCATACCCGTTTGCATGTACTTTATGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGATCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGAGCGTAGATGGATGTTTAAGTCAGTTGTGAAAGTTTGCGGCTCAACCGTAAAATTGCAGTTGATACTGGATATCTTGAGTGCAGTTGAGGCAGGCGGAATTCGTGGTGTAGCGGTGAAATGCTTAGATATCACGAGGAACTCCGATTGCGAAGGCAGCCTGCTAAGCTGCAACTGACATTGAGGCTCGAAAGTGTGGGTATCAAACAGG\"      \n",
       "[24] \"TAGGGAATCTTCGGCAATGGACGGAAGTCTGACCGAGCAACGCCGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAGCTCTGTTGTAAGAGAAGAACGAGTGTGAGAGTGGAAAGTTCACACTGTGACGGTATCTTACCAGAAAGGGACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTCCCGAGCGTTGTCCGGATTTATTGGGCGTAAAGCGAGCGCAGGCGGTTAGATAAGTCTGAAGTTAAAGGCTGTGGCTTAACCATAGTAGGCTTTGGAAACTGTTTAACTTGAGTGCAAGAGGGGAGAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAGGAACACCGGTGGCGAAAGCGGCTCTCTGGCTTGTAACTGACGCTGAGGCTCGAAAGCGTGGGGAGCAAACAGG\" \n",
       "[25] \"TGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCAACGCCGCGTGAGTGATGACGGTCTTCGGATTGTAAAGCTCTGTCTTCAGGGACGATAATGACGGTACCTGAGGAGGAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGATTTACTGGGCGTAAAGGGAGCGTAGGTGGATATTTAAGTGGGATGTGAAATACTCGGGCTTAACCTGGGTGCTGCATTCCAAACTGGATATCTAGAGTGCAGGAGAGGAAAGTAGAATTCTTAGTGTAGCGGTGAAATGCGTAGAGATTAGGAAGAATACCAGTGGCGAAGGCGACTTTCTGGACTGTAACTGACACTGAGGCTCGAAAGCGTGGGGAGCAAACAGG\"                          "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "e3.f$control.taxa.sequences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A txnmyTbl: 25 × 7 of type txnmyTbl</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>Kingdom</th><th scope=col>Phylum</th><th scope=col>Class</th><th scope=col>Order</th><th scope=col>Family</th><th scope=col>Genus</th><th scope=col>Species</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>Bacteria</td><td>Firmicutes         </td><td>Bacilli              </td><td>Lactobacillales  </td><td>Streptococcaceae    </td><td>Streptococcus            </td><td>mutans                                </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Proteobacteria     </td><td>Gammaproteobacteria  </td><td>Enterobacteriales</td><td>Enterobacteriaceae  </td><td>Escherichia/Shigella     </td><td>NA                                    </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Firmicutes         </td><td>Bacilli              </td><td>Bacillales       </td><td>Staphylococcaceae   </td><td>Staphylococcus           </td><td>NA                                    </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Firmicutes         </td><td>Bacilli              </td><td>Lactobacillales  </td><td>Lactobacillaceae    </td><td>Lactobacillus            </td><td>gasseri/johnsonii                     </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Proteobacteria     </td><td>Alphaproteobacteria  </td><td>Rhodobacterales  </td><td>Rhodobacteraceae    </td><td>Rhodobacter              </td><td>johrii/megalophilus/ovatus/sphaeroides</td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Proteobacteria     </td><td>Gammaproteobacteria  </td><td>Pseudomonadales  </td><td>Pseudomonadaceae    </td><td>Pseudomonas              </td><td>NA                                    </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Firmicutes         </td><td>Clostridia           </td><td>Clostridiales    </td><td>Clostridiaceae_1    </td><td>Clostridium_sensu_stricto</td><td>NA                                    </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Firmicutes         </td><td>Bacilli              </td><td>Lactobacillales  </td><td>Streptococcaceae    </td><td>Streptococcus            </td><td>agalactiae/dysgalactiae               </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Proteobacteria     </td><td>Epsilonproteobacteria</td><td>Campylobacterales</td><td>Helicobacteraceae   </td><td>Helicobacter             </td><td>pylori                                </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Proteobacteria     </td><td>Betaproteobacteria   </td><td>Neisseriales     </td><td>Neisseriaceae       </td><td>Neisseria                </td><td>meningitidis                          </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Deinococcus-Thermus</td><td>Deinococci           </td><td>Deinococcales    </td><td>Deinococcaceae      </td><td>Deinococcus              </td><td>radiodurans                           </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Proteobacteria     </td><td>Gammaproteobacteria  </td><td>Pseudomonadales  </td><td>Moraxellaceae       </td><td>Acinetobacter            </td><td>baumannii                             </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Bacteroidetes      </td><td>Bacteroidia          </td><td>Bacteroidales    </td><td>Bacteroidaceae      </td><td>Bacteroides              </td><td>dorei/vulgatus                        </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Firmicutes         </td><td>Bacilli              </td><td>Bacillales       </td><td>Bacillaceae_1       </td><td>Bacillus                 </td><td>NA                                    </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Firmicutes         </td><td>Bacilli              </td><td>Bacillales       </td><td>Staphylococcaceae   </td><td>Staphylococcus           </td><td>NA                                    </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Firmicutes         </td><td>Bacilli              </td><td>Bacillales       </td><td>Staphylococcaceae   </td><td>Staphylococcus           </td><td>epidermidis                           </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Firmicutes         </td><td>Bacilli              </td><td>Bacillales       </td><td>Listeriaceae        </td><td>Listeria                 </td><td>NA                                    </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Actinobacteria     </td><td>Actinobacteria       </td><td>Actinomycetales  </td><td>Propionibacteriaceae</td><td>Propionibacterium        </td><td>acnes                                 </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Firmicutes         </td><td>Bacilli              </td><td>Lactobacillales  </td><td>Enterococcaceae     </td><td>Enterococcus             </td><td>durans/faecalis/faecium               </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Bacteroidetes      </td><td>Bacteroidia          </td><td>Bacteroidales    </td><td>Bacteroidaceae      </td><td>Bacteroides              </td><td>vulgatus                              </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Actinobacteria     </td><td>Actinobacteria       </td><td>Actinomycetales  </td><td>Actinomycetaceae    </td><td>Actinomyces              </td><td>NA                                    </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Bacteroidetes      </td><td>Bacteroidia          </td><td>Bacteroidales    </td><td>Bacteroidaceae      </td><td>Bacteroides              </td><td>vulgatus                              </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Bacteroidetes      </td><td>Bacteroidia          </td><td>Bacteroidales    </td><td>Bacteroidaceae      </td><td>Bacteroides              </td><td>vulgatus                              </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Firmicutes         </td><td>Bacilli              </td><td>Lactobacillales  </td><td>Streptococcaceae    </td><td>Streptococcus            </td><td>pneumoniae/pseudopneumoniae           </td></tr>\n",
       "\t<tr><td>Bacteria</td><td>Firmicutes         </td><td>Clostridia           </td><td>Clostridiales    </td><td>Clostridiaceae_1    </td><td>Clostridium_sensu_stricto</td><td>beijerinckii                          </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A txnmyTbl: 25 × 7 of type txnmyTbl\n",
       "\\begin{tabular}{lllllll}\n",
       " Kingdom & Phylum & Class & Order & Family & Genus & Species\\\\\n",
       "\\hline\n",
       "\t Bacteria & Firmicutes          & Bacilli               & Lactobacillales   & Streptococcaceae     & Streptococcus             & mutans                                \\\\\n",
       "\t Bacteria & Proteobacteria      & Gammaproteobacteria   & Enterobacteriales & Enterobacteriaceae   & Escherichia/Shigella      & NA                                    \\\\\n",
       "\t Bacteria & Firmicutes          & Bacilli               & Bacillales        & Staphylococcaceae    & Staphylococcus            & NA                                    \\\\\n",
       "\t Bacteria & Firmicutes          & Bacilli               & Lactobacillales   & Lactobacillaceae     & Lactobacillus             & gasseri/johnsonii                     \\\\\n",
       "\t Bacteria & Proteobacteria      & Alphaproteobacteria   & Rhodobacterales   & Rhodobacteraceae     & Rhodobacter               & johrii/megalophilus/ovatus/sphaeroides\\\\\n",
       "\t Bacteria & Proteobacteria      & Gammaproteobacteria   & Pseudomonadales   & Pseudomonadaceae     & Pseudomonas               & NA                                    \\\\\n",
       "\t Bacteria & Firmicutes          & Clostridia            & Clostridiales     & Clostridiaceae\\_1     & Clostridium\\_sensu\\_stricto & NA                                    \\\\\n",
       "\t Bacteria & Firmicutes          & Bacilli               & Lactobacillales   & Streptococcaceae     & Streptococcus             & agalactiae/dysgalactiae               \\\\\n",
       "\t Bacteria & Proteobacteria      & Epsilonproteobacteria & Campylobacterales & Helicobacteraceae    & Helicobacter              & pylori                                \\\\\n",
       "\t Bacteria & Proteobacteria      & Betaproteobacteria    & Neisseriales      & Neisseriaceae        & Neisseria                 & meningitidis                          \\\\\n",
       "\t Bacteria & Deinococcus-Thermus & Deinococci            & Deinococcales     & Deinococcaceae       & Deinococcus               & radiodurans                           \\\\\n",
       "\t Bacteria & Proteobacteria      & Gammaproteobacteria   & Pseudomonadales   & Moraxellaceae        & Acinetobacter             & baumannii                             \\\\\n",
       "\t Bacteria & Bacteroidetes       & Bacteroidia           & Bacteroidales     & Bacteroidaceae       & Bacteroides               & dorei/vulgatus                        \\\\\n",
       "\t Bacteria & Firmicutes          & Bacilli               & Bacillales        & Bacillaceae\\_1        & Bacillus                  & NA                                    \\\\\n",
       "\t Bacteria & Firmicutes          & Bacilli               & Bacillales        & Staphylococcaceae    & Staphylococcus            & NA                                    \\\\\n",
       "\t Bacteria & Firmicutes          & Bacilli               & Bacillales        & Staphylococcaceae    & Staphylococcus            & epidermidis                           \\\\\n",
       "\t Bacteria & Firmicutes          & Bacilli               & Bacillales        & Listeriaceae         & Listeria                  & NA                                    \\\\\n",
       "\t Bacteria & Actinobacteria      & Actinobacteria        & Actinomycetales   & Propionibacteriaceae & Propionibacterium         & acnes                                 \\\\\n",
       "\t Bacteria & Firmicutes          & Bacilli               & Lactobacillales   & Enterococcaceae      & Enterococcus              & durans/faecalis/faecium               \\\\\n",
       "\t Bacteria & Bacteroidetes       & Bacteroidia           & Bacteroidales     & Bacteroidaceae       & Bacteroides               & vulgatus                              \\\\\n",
       "\t Bacteria & Actinobacteria      & Actinobacteria        & Actinomycetales   & Actinomycetaceae     & Actinomyces               & NA                                    \\\\\n",
       "\t Bacteria & Bacteroidetes       & Bacteroidia           & Bacteroidales     & Bacteroidaceae       & Bacteroides               & vulgatus                              \\\\\n",
       "\t Bacteria & Bacteroidetes       & Bacteroidia           & Bacteroidales     & Bacteroidaceae       & Bacteroides               & vulgatus                              \\\\\n",
       "\t Bacteria & Firmicutes          & Bacilli               & Lactobacillales   & Streptococcaceae     & Streptococcus             & pneumoniae/pseudopneumoniae           \\\\\n",
       "\t Bacteria & Firmicutes          & Clostridia            & Clostridiales     & Clostridiaceae\\_1     & Clostridium\\_sensu\\_stricto & beijerinckii                          \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A txnmyTbl: 25 × 7 of type txnmyTbl\n",
       "\n",
       "| Kingdom | Phylum | Class | Order | Family | Genus | Species |\n",
       "|---|---|---|---|---|---|---|\n",
       "| Bacteria | Firmicutes          | Bacilli               | Lactobacillales   | Streptococcaceae     | Streptococcus             | mutans                                 |\n",
       "| Bacteria | Proteobacteria      | Gammaproteobacteria   | Enterobacteriales | Enterobacteriaceae   | Escherichia/Shigella      | NA                                     |\n",
       "| Bacteria | Firmicutes          | Bacilli               | Bacillales        | Staphylococcaceae    | Staphylococcus            | NA                                     |\n",
       "| Bacteria | Firmicutes          | Bacilli               | Lactobacillales   | Lactobacillaceae     | Lactobacillus             | gasseri/johnsonii                      |\n",
       "| Bacteria | Proteobacteria      | Alphaproteobacteria   | Rhodobacterales   | Rhodobacteraceae     | Rhodobacter               | johrii/megalophilus/ovatus/sphaeroides |\n",
       "| Bacteria | Proteobacteria      | Gammaproteobacteria   | Pseudomonadales   | Pseudomonadaceae     | Pseudomonas               | NA                                     |\n",
       "| Bacteria | Firmicutes          | Clostridia            | Clostridiales     | Clostridiaceae_1     | Clostridium_sensu_stricto | NA                                     |\n",
       "| Bacteria | Firmicutes          | Bacilli               | Lactobacillales   | Streptococcaceae     | Streptococcus             | agalactiae/dysgalactiae                |\n",
       "| Bacteria | Proteobacteria      | Epsilonproteobacteria | Campylobacterales | Helicobacteraceae    | Helicobacter              | pylori                                 |\n",
       "| Bacteria | Proteobacteria      | Betaproteobacteria    | Neisseriales      | Neisseriaceae        | Neisseria                 | meningitidis                           |\n",
       "| Bacteria | Deinococcus-Thermus | Deinococci            | Deinococcales     | Deinococcaceae       | Deinococcus               | radiodurans                            |\n",
       "| Bacteria | Proteobacteria      | Gammaproteobacteria   | Pseudomonadales   | Moraxellaceae        | Acinetobacter             | baumannii                              |\n",
       "| Bacteria | Bacteroidetes       | Bacteroidia           | Bacteroidales     | Bacteroidaceae       | Bacteroides               | dorei/vulgatus                         |\n",
       "| Bacteria | Firmicutes          | Bacilli               | Bacillales        | Bacillaceae_1        | Bacillus                  | NA                                     |\n",
       "| Bacteria | Firmicutes          | Bacilli               | Bacillales        | Staphylococcaceae    | Staphylococcus            | NA                                     |\n",
       "| Bacteria | Firmicutes          | Bacilli               | Bacillales        | Staphylococcaceae    | Staphylococcus            | epidermidis                            |\n",
       "| Bacteria | Firmicutes          | Bacilli               | Bacillales        | Listeriaceae         | Listeria                  | NA                                     |\n",
       "| Bacteria | Actinobacteria      | Actinobacteria        | Actinomycetales   | Propionibacteriaceae | Propionibacterium         | acnes                                  |\n",
       "| Bacteria | Firmicutes          | Bacilli               | Lactobacillales   | Enterococcaceae      | Enterococcus              | durans/faecalis/faecium                |\n",
       "| Bacteria | Bacteroidetes       | Bacteroidia           | Bacteroidales     | Bacteroidaceae       | Bacteroides               | vulgatus                               |\n",
       "| Bacteria | Actinobacteria      | Actinobacteria        | Actinomycetales   | Actinomycetaceae     | Actinomyces               | NA                                     |\n",
       "| Bacteria | Bacteroidetes       | Bacteroidia           | Bacteroidales     | Bacteroidaceae       | Bacteroides               | vulgatus                               |\n",
       "| Bacteria | Bacteroidetes       | Bacteroidia           | Bacteroidales     | Bacteroidaceae       | Bacteroides               | vulgatus                               |\n",
       "| Bacteria | Firmicutes          | Bacilli               | Lactobacillales   | Streptococcaceae     | Streptococcus             | pneumoniae/pseudopneumoniae            |\n",
       "| Bacteria | Firmicutes          | Clostridia            | Clostridiales     | Clostridiaceae_1     | Clostridium_sensu_stricto | beijerinckii                           |\n",
       "\n"
      ],
      "text/plain": [
       "      Kingdom  Phylum              Class                 Order            \n",
       " [1,] Bacteria Firmicutes          Bacilli               Lactobacillales  \n",
       " [2,] Bacteria Proteobacteria      Gammaproteobacteria   Enterobacteriales\n",
       " [3,] Bacteria Firmicutes          Bacilli               Bacillales       \n",
       " [4,] Bacteria Firmicutes          Bacilli               Lactobacillales  \n",
       " [5,] Bacteria Proteobacteria      Alphaproteobacteria   Rhodobacterales  \n",
       " [6,] Bacteria Proteobacteria      Gammaproteobacteria   Pseudomonadales  \n",
       " [7,] Bacteria Firmicutes          Clostridia            Clostridiales    \n",
       " [8,] Bacteria Firmicutes          Bacilli               Lactobacillales  \n",
       " [9,] Bacteria Proteobacteria      Epsilonproteobacteria Campylobacterales\n",
       "[10,] Bacteria Proteobacteria      Betaproteobacteria    Neisseriales     \n",
       "[11,] Bacteria Deinococcus-Thermus Deinococci            Deinococcales    \n",
       "[12,] Bacteria Proteobacteria      Gammaproteobacteria   Pseudomonadales  \n",
       "[13,] Bacteria Bacteroidetes       Bacteroidia           Bacteroidales    \n",
       "[14,] Bacteria Firmicutes          Bacilli               Bacillales       \n",
       "[15,] Bacteria Firmicutes          Bacilli               Bacillales       \n",
       "[16,] Bacteria Firmicutes          Bacilli               Bacillales       \n",
       "[17,] Bacteria Firmicutes          Bacilli               Bacillales       \n",
       "[18,] Bacteria Actinobacteria      Actinobacteria        Actinomycetales  \n",
       "[19,] Bacteria Firmicutes          Bacilli               Lactobacillales  \n",
       "[20,] Bacteria Bacteroidetes       Bacteroidia           Bacteroidales    \n",
       "[21,] Bacteria Actinobacteria      Actinobacteria        Actinomycetales  \n",
       "[22,] Bacteria Bacteroidetes       Bacteroidia           Bacteroidales    \n",
       "[23,] Bacteria Bacteroidetes       Bacteroidia           Bacteroidales    \n",
       "[24,] Bacteria Firmicutes          Bacilli               Lactobacillales  \n",
       "[25,] Bacteria Firmicutes          Clostridia            Clostridiales    \n",
       "      Family               Genus                    \n",
       " [1,] Streptococcaceae     Streptococcus            \n",
       " [2,] Enterobacteriaceae   Escherichia/Shigella     \n",
       " [3,] Staphylococcaceae    Staphylococcus           \n",
       " [4,] Lactobacillaceae     Lactobacillus            \n",
       " [5,] Rhodobacteraceae     Rhodobacter              \n",
       " [6,] Pseudomonadaceae     Pseudomonas              \n",
       " [7,] Clostridiaceae_1     Clostridium_sensu_stricto\n",
       " [8,] Streptococcaceae     Streptococcus            \n",
       " [9,] Helicobacteraceae    Helicobacter             \n",
       "[10,] Neisseriaceae        Neisseria                \n",
       "[11,] Deinococcaceae       Deinococcus              \n",
       "[12,] Moraxellaceae        Acinetobacter            \n",
       "[13,] Bacteroidaceae       Bacteroides              \n",
       "[14,] Bacillaceae_1        Bacillus                 \n",
       "[15,] Staphylococcaceae    Staphylococcus           \n",
       "[16,] Staphylococcaceae    Staphylococcus           \n",
       "[17,] Listeriaceae         Listeria                 \n",
       "[18,] Propionibacteriaceae Propionibacterium        \n",
       "[19,] Enterococcaceae      Enterococcus             \n",
       "[20,] Bacteroidaceae       Bacteroides              \n",
       "[21,] Actinomycetaceae     Actinomyces              \n",
       "[22,] Bacteroidaceae       Bacteroides              \n",
       "[23,] Bacteroidaceae       Bacteroides              \n",
       "[24,] Streptococcaceae     Streptococcus            \n",
       "[25,] Clostridiaceae_1     Clostridium_sensu_stricto\n",
       "      Species                               \n",
       " [1,] mutans                                \n",
       " [2,] NA                                    \n",
       " [3,] NA                                    \n",
       " [4,] gasseri/johnsonii                     \n",
       " [5,] johrii/megalophilus/ovatus/sphaeroides\n",
       " [6,] NA                                    \n",
       " [7,] NA                                    \n",
       " [8,] agalactiae/dysgalactiae               \n",
       " [9,] pylori                                \n",
       "[10,] meningitidis                          \n",
       "[11,] radiodurans                           \n",
       "[12,] baumannii                             \n",
       "[13,] dorei/vulgatus                        \n",
       "[14,] NA                                    \n",
       "[15,] NA                                    \n",
       "[16,] epidermidis                           \n",
       "[17,] NA                                    \n",
       "[18,] acnes                                 \n",
       "[19,] durans/faecalis/faecium               \n",
       "[20,] vulgatus                              \n",
       "[21,] NA                                    \n",
       "[22,] vulgatus                              \n",
       "[23,] vulgatus                              \n",
       "[24,] pneumoniae/pseudopneumoniae           \n",
       "[25,] beijerinckii                          "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "e3.f$taxonomy.of.control.taxa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A matrix: 15 × 5 of type dbl[,5]</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>unfiltered.read.count</th><th scope=col>WSfiltered.read.count</th><th scope=col>WSfiltered.read.percent</th><th scope=col>ASfiltered.read.count</th><th scope=col>ASfiltered.read.percent</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>233</th><td>104899</td><td>104075</td><td> 99.21448</td><td>103715</td><td>98.87130</td></tr>\n",
       "\t<tr><th scope=row>234</th><td>182190</td><td>180268</td><td> 98.94506</td><td>177580</td><td>97.46967</td></tr>\n",
       "\t<tr><th scope=row>235</th><td> 19112</td><td> 19057</td><td> 99.71222</td><td> 18655</td><td>97.60883</td></tr>\n",
       "\t<tr><th scope=row>236</th><td> 41766</td><td> 41375</td><td> 99.06383</td><td> 39988</td><td>95.74295</td></tr>\n",
       "\t<tr><th scope=row>237</th><td> 37673</td><td> 37216</td><td> 98.78693</td><td> 15648</td><td>41.53638</td></tr>\n",
       "\t<tr><th scope=row>238</th><td> 10183</td><td> 10163</td><td> 99.80359</td><td>  9491</td><td>93.20436</td></tr>\n",
       "\t<tr><th scope=row>239</th><td>  2388</td><td>  2388</td><td>100.00000</td><td>  2339</td><td>97.94807</td></tr>\n",
       "\t<tr><th scope=row>24</th><td>  1861</td><td>  1861</td><td>100.00000</td><td>  1841</td><td>98.92531</td></tr>\n",
       "\t<tr><th scope=row>240</th><td> 14054</td><td> 14018</td><td> 99.74385</td><td> 13715</td><td>97.58788</td></tr>\n",
       "\t<tr><th scope=row>241</th><td> 19769</td><td> 19709</td><td> 99.69649</td><td> 19007</td><td>96.14548</td></tr>\n",
       "\t<tr><th scope=row>242</th><td> 20498</td><td> 20388</td><td> 99.46336</td><td> 20334</td><td>99.19992</td></tr>\n",
       "\t<tr><th scope=row>244</th><td>127966</td><td>127317</td><td> 99.49283</td><td>124757</td><td>97.49230</td></tr>\n",
       "\t<tr><th scope=row>245</th><td> 22849</td><td> 22746</td><td> 99.54921</td><td> 22288</td><td>97.54475</td></tr>\n",
       "\t<tr><th scope=row>246</th><td>  3180</td><td>  3180</td><td>100.00000</td><td>  3157</td><td>99.27673</td></tr>\n",
       "\t<tr><th scope=row>247</th><td>  2917</td><td>  2917</td><td>100.00000</td><td>  2813</td><td>96.43469</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A matrix: 15 × 5 of type dbl{[},5{]}\n",
       "\\begin{tabular}{r|lllll}\n",
       "  & unfiltered.read.count & WSfiltered.read.count & WSfiltered.read.percent & ASfiltered.read.count & ASfiltered.read.percent\\\\\n",
       "\\hline\n",
       "\t233 & 104899 & 104075 &  99.21448 & 103715 & 98.87130\\\\\n",
       "\t234 & 182190 & 180268 &  98.94506 & 177580 & 97.46967\\\\\n",
       "\t235 &  19112 &  19057 &  99.71222 &  18655 & 97.60883\\\\\n",
       "\t236 &  41766 &  41375 &  99.06383 &  39988 & 95.74295\\\\\n",
       "\t237 &  37673 &  37216 &  98.78693 &  15648 & 41.53638\\\\\n",
       "\t238 &  10183 &  10163 &  99.80359 &   9491 & 93.20436\\\\\n",
       "\t239 &   2388 &   2388 & 100.00000 &   2339 & 97.94807\\\\\n",
       "\t24 &   1861 &   1861 & 100.00000 &   1841 & 98.92531\\\\\n",
       "\t240 &  14054 &  14018 &  99.74385 &  13715 & 97.58788\\\\\n",
       "\t241 &  19769 &  19709 &  99.69649 &  19007 & 96.14548\\\\\n",
       "\t242 &  20498 &  20388 &  99.46336 &  20334 & 99.19992\\\\\n",
       "\t244 & 127966 & 127317 &  99.49283 & 124757 & 97.49230\\\\\n",
       "\t245 &  22849 &  22746 &  99.54921 &  22288 & 97.54475\\\\\n",
       "\t246 &   3180 &   3180 & 100.00000 &   3157 & 99.27673\\\\\n",
       "\t247 &   2917 &   2917 & 100.00000 &   2813 & 96.43469\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A matrix: 15 × 5 of type dbl[,5]\n",
       "\n",
       "| <!--/--> | unfiltered.read.count | WSfiltered.read.count | WSfiltered.read.percent | ASfiltered.read.count | ASfiltered.read.percent |\n",
       "|---|---|---|---|---|---|\n",
       "| 233 | 104899 | 104075 |  99.21448 | 103715 | 98.87130 |\n",
       "| 234 | 182190 | 180268 |  98.94506 | 177580 | 97.46967 |\n",
       "| 235 |  19112 |  19057 |  99.71222 |  18655 | 97.60883 |\n",
       "| 236 |  41766 |  41375 |  99.06383 |  39988 | 95.74295 |\n",
       "| 237 |  37673 |  37216 |  98.78693 |  15648 | 41.53638 |\n",
       "| 238 |  10183 |  10163 |  99.80359 |   9491 | 93.20436 |\n",
       "| 239 |   2388 |   2388 | 100.00000 |   2339 | 97.94807 |\n",
       "| 24 |   1861 |   1861 | 100.00000 |   1841 | 98.92531 |\n",
       "| 240 |  14054 |  14018 |  99.74385 |  13715 | 97.58788 |\n",
       "| 241 |  19769 |  19709 |  99.69649 |  19007 | 96.14548 |\n",
       "| 242 |  20498 |  20388 |  99.46336 |  20334 | 99.19992 |\n",
       "| 244 | 127966 | 127317 |  99.49283 | 124757 | 97.49230 |\n",
       "| 245 |  22849 |  22746 |  99.54921 |  22288 | 97.54475 |\n",
       "| 246 |   3180 |   3180 | 100.00000 |   3157 | 99.27673 |\n",
       "| 247 |   2917 |   2917 | 100.00000 |   2813 | 96.43469 |\n",
       "\n"
      ],
      "text/plain": [
       "    unfiltered.read.count WSfiltered.read.count WSfiltered.read.percent\n",
       "233 104899                104075                 99.21448              \n",
       "234 182190                180268                 98.94506              \n",
       "235  19112                 19057                 99.71222              \n",
       "236  41766                 41375                 99.06383              \n",
       "237  37673                 37216                 98.78693              \n",
       "238  10183                 10163                 99.80359              \n",
       "239   2388                  2388                100.00000              \n",
       "24    1861                  1861                100.00000              \n",
       "240  14054                 14018                 99.74385              \n",
       "241  19769                 19709                 99.69649              \n",
       "242  20498                 20388                 99.46336              \n",
       "244 127966                127317                 99.49283              \n",
       "245  22849                 22746                 99.54921              \n",
       "246   3180                  3180                100.00000              \n",
       "247   2917                  2917                100.00000              \n",
       "    ASfiltered.read.count ASfiltered.read.percent\n",
       "233 103715                98.87130               \n",
       "234 177580                97.46967               \n",
       "235  18655                97.60883               \n",
       "236  39988                95.74295               \n",
       "237  15648                41.53638               \n",
       "238   9491                93.20436               \n",
       "239   2339                97.94807               \n",
       "24    1841                98.92531               \n",
       "240  13715                97.58788               \n",
       "241  19007                96.14548               \n",
       "242  20334                99.19992               \n",
       "244 124757                97.49230               \n",
       "245  22288                97.54475               \n",
       "246   3157                99.27673               \n",
       "247   2813                96.43469               "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "e3.f$read.count.table[135:149, ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
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   "outputs": [
    {
     "data": {
      "text/html": [
       "719.91048"
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       "719.91048"
      ],
      "text/markdown": [
       "719.91048"
      ],
      "text/plain": [
       "[1] 719.9105"
      ]
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     "metadata": {},
     "output_type": "display_data"
    }
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   "source": [
    "e3.f$relative.abundance.filter.read.count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": true
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   "outputs": [
    {
     "data": {
      "text/html": [
       "6.94"
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       "6.94"
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       "6.94"
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       "[1] 6.94"
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   "source": [
    "e3.f$prevalence.filter.sample.count"
   ]
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  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "phyloseq-class experiment-level object\n",
       "otu_table()   OTU Table:         [ 152 taxa and 347 samples ]\n",
       "sample_data() Sample Data:       [ 347 samples by 9 sample variables ]\n",
       "tax_table()   Taxonomy Table:    [ 152 taxa by 7 taxonomic ranks ]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(e3f <- e3.f$filtered.phyloseq)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hey, that looks like a pretty tidied up dataset! Let's say that we want to remove samples from a specific visit and those that tested positive for gonorrhea? __microfilter__ works great wtih standard dplyr pipe operators."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Removing 28 samples matching metadata identifiers Visit:1.1\n",
      "Removing 3 samples matching metadata identifiers Site:gnc\n"
     ]
    }
   ],
   "source": [
    "e3f %>%\n",
    "  microfilter(mdFACTOR = \"1.1\", mdCAT = \"Visit\") %>%\n",
    "  microfilter(mdFACTOR = \"gnc\", mdCAT = \"Site\") -> e3f.noghon"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, let's subset our filtered dataset to include only samples that were collected during the first week of the study. We can enable negative metadata filtering via the __microfilter__ function with the flag mdNEGATIVE."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Removing 133 samples not matching metadata identifiers Visit:0\n"
     ]
    }
   ],
   "source": [
    "E3F <- microfilter(ps = e3f.noghon, mdCAT = \"Visit\", mdFACTOR = \"0\", mdNEGATIVE = TRUE, return.all = FALSE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "phyloseq-class experiment-level object\n",
       "otu_table()   OTU Table:         [ 152 taxa and 183 samples ]\n",
       "sample_data() Sample Data:       [ 183 samples by 9 sample variables ]\n",
       "tax_table()   Taxonomy Table:    [ 152 taxa by 7 taxonomic ranks ]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "E3F"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Processing and exporting\n",
    "<br>Now that we've filtered the dataset to our liking, we'll export all of the data associated with our final, filtered dataset using the __write.dataset__ function. Unfortunately, I've never been able to get the biomformat package (v1.8.0) to play nice with my datasets. In case the kinks get worked out, I'd recommend using the __write.dataset.biom__ function to export your dataset directly to biom format. Until then, we'll use __write.dataset__ to perform some final minor modifications and export our dataset. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"write.dataset\"></a>\n",
    "# write.dataset, write.dataset.biom\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>WRITE.DATASET, WRITE.DATASET.BIOM</b><br>\n",
    "Exporting functions for writing marker gene datasets to external files.<br>\n",
    "<br>\n",
    "<b>Input:</b> <br>\n",
    "<b>ps:</b> a phyloseq-class dataset.<br>\n",
    "<br>\n",
    "<b>Parameters:</b><br>\n",
    "<b>filePATH:</b> The filepath where output should be written.<br>\n",
    "<b>filePREFIX:</b> The prefix identifier for all output written.<br>\n",
    "<b>writeFASTA:</b> A logical flag indicating if ASV sequences should be written to an external FASTA file. Generally, a good idea, but can be time consuming if 1000s of taxa remain in your dataset when writing. Default is TRUE.<br>\n",
    "<b>rename:</b> A logical flag indicating if ASV identifiers should be renamed to ASV1, ASV2, ..., ASVN. Default is FALSE.<br>\n",
    "<br>\n",
    "<b>Output:</b> <br>\n",
    "<b>_ASVs.fasta:</b>  FASTA of all ASV sequences. Even if rename=FALSE, FASTA identifiers are labeled ASV1, ASV2,... <br>\n",
    "<br>\n",
    "<b>write.dataset.biom:</b><br>\n",
    "<b>_ASV_table.biom:</b> A biom file with observation and sample metadata integrated. I've run into problems attempting to import the resulting biom back into phyloseq, but this might warrant a closer look with a newer version. <br>\n",
    "<br>\n",
    "<b>write.dataset:</b><br>\n",
    "<b>_ASV_table.txt:</b>  A standard count table (eg. OTU table) of read counts of taxa (ASVs) across all samples. <br>\n",
    "<b>_ASV_taxonomy.txt:</b> A taxonomy table with the sequence identifier (eg. ASV1) in the first column and semicolon-separated taxonomy in the second column.<br>\n",
    "<b>_sample_data.txt:</b> A sample data table of all associated metadata. \n",
    "<br>\n",
    "\n",
    "</div>\n",
    "<br>\n",
    "<div class=\"alert alert-block alert-success\">\n",
    "<b>TIP:</b> Before writing, all files written by <b>write.dataset</b> are formatted for easy merging into a biom file using the  <A HREF = \"http://biom-format.org/documentation/biom_conversion.html\">standalone biom package</A> without any further manipulation. \n",
    "</div>\n",
    "\n",
    "Now, we'll use <b>write.dataset</b> to write the desired data to external files in the location specified and, because we've flagged the function to rename the ASVs in the dataset, we'll specify a new R object that will be identical to the previous phyloseq dataset, but with the ASVs renamed. Otherwise, we could just run the function without defining a new object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"/Users/bpb/Desktop/microfiltR/microfiltR_vignette/e3.f_ASVs.fasta\"\n",
      "[1] \"/Users/bpb/Desktop/microfiltR/microfiltR_vignette/e3.f_ASV_table.txt\"\n",
      "[1] \"/Users/bpb/Desktop/microfiltR/microfiltR_vignette/e3.f_ASV_taxonomy.txt\"\n",
      "[1] \"/Users/bpb/Desktop/microfiltR/microfiltR_vignette/e3.f_sample_data.txt\"\n"
     ]
    }
   ],
   "source": [
    "fp <- paste(getwd(), \"/\", sep = \"\")\n",
    "e3f.f <- write.dataset(ps = e3f, filePATH = fp, filePREFIX = \"e3.f\", writeFASTA=TRUE, rename = TRUE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Boom! We've now written all of the metadata associated with our filtered marker gene study to various output files. Now, let's take a final peek at our ASV count table in a format that's a little more friendly on the eyes. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A otu_tabl: 10 × 10 of type otu_tabl</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>ASV1</th><th scope=col>ASV2</th><th scope=col>ASV3</th><th scope=col>ASV4</th><th scope=col>ASV5</th><th scope=col>ASV6</th><th scope=col>ASV7</th><th scope=col>ASV8</th><th scope=col>ASV9</th><th scope=col>ASV10</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>   16</td><td>    0</td><td>    0</td><td>   0</td><td>160</td><td>   0</td><td>  0</td><td>  0</td><td>685</td><td>  0</td></tr>\n",
       "\t<tr><th scope=row>10</th><td>    0</td><td>  244</td><td>    0</td><td>   0</td><td>536</td><td>  48</td><td>  0</td><td>  0</td><td>  0</td><td>162</td></tr>\n",
       "\t<tr><th scope=row>100</th><td>  251</td><td>31618</td><td>    0</td><td>   0</td><td>  0</td><td>   0</td><td>705</td><td>  0</td><td>396</td><td>  0</td></tr>\n",
       "\t<tr><th scope=row>101</th><td>15722</td><td>    0</td><td> 6603</td><td>   0</td><td>  0</td><td>   0</td><td>  0</td><td>  0</td><td>  0</td><td>  0</td></tr>\n",
       "\t<tr><th scope=row>102</th><td> 1993</td><td>    0</td><td>    0</td><td>   0</td><td> 58</td><td>  39</td><td>  0</td><td>  0</td><td>  0</td><td>  0</td></tr>\n",
       "\t<tr><th scope=row>103</th><td>   81</td><td>    0</td><td>    0</td><td>   0</td><td>  0</td><td> 169</td><td>  0</td><td>  0</td><td>  0</td><td>103</td></tr>\n",
       "\t<tr><th scope=row>104</th><td>  326</td><td>    0</td><td>18871</td><td>   0</td><td>  0</td><td>   0</td><td>  0</td><td>  0</td><td>  0</td><td>  0</td></tr>\n",
       "\t<tr><th scope=row>106</th><td>   11</td><td>    0</td><td>  500</td><td>   0</td><td>  0</td><td>   0</td><td>  4</td><td>  0</td><td>  0</td><td>  0</td></tr>\n",
       "\t<tr><th scope=row>107</th><td>   38</td><td>    0</td><td>    0</td><td>   0</td><td>343</td><td>   0</td><td> 60</td><td> 76</td><td>  0</td><td>  0</td></tr>\n",
       "\t<tr><th scope=row>108</th><td> 8064</td><td>  125</td><td>    0</td><td>1095</td><td>457</td><td>1378</td><td>530</td><td>239</td><td>  0</td><td>846</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A otu_tabl: 10 × 10 of type otu\\_tabl\n",
       "\\begin{tabular}{r|llllllllll}\n",
       "  & ASV1 & ASV2 & ASV3 & ASV4 & ASV5 & ASV6 & ASV7 & ASV8 & ASV9 & ASV10\\\\\n",
       "\\hline\n",
       "\t1 &    16 &     0 &     0 &    0 & 160 &    0 &   0 &   0 & 685 &   0\\\\\n",
       "\t10 &     0 &   244 &     0 &    0 & 536 &   48 &   0 &   0 &   0 & 162\\\\\n",
       "\t100 &   251 & 31618 &     0 &    0 &   0 &    0 & 705 &   0 & 396 &   0\\\\\n",
       "\t101 & 15722 &     0 &  6603 &    0 &   0 &    0 &   0 &   0 &   0 &   0\\\\\n",
       "\t102 &  1993 &     0 &     0 &    0 &  58 &   39 &   0 &   0 &   0 &   0\\\\\n",
       "\t103 &    81 &     0 &     0 &    0 &   0 &  169 &   0 &   0 &   0 & 103\\\\\n",
       "\t104 &   326 &     0 & 18871 &    0 &   0 &    0 &   0 &   0 &   0 &   0\\\\\n",
       "\t106 &    11 &     0 &   500 &    0 &   0 &    0 &   4 &   0 &   0 &   0\\\\\n",
       "\t107 &    38 &     0 &     0 &    0 & 343 &    0 &  60 &  76 &   0 &   0\\\\\n",
       "\t108 &  8064 &   125 &     0 & 1095 & 457 & 1378 & 530 & 239 &   0 & 846\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A otu_tabl: 10 × 10 of type otu_tabl\n",
       "\n",
       "| <!--/--> | ASV1 | ASV2 | ASV3 | ASV4 | ASV5 | ASV6 | ASV7 | ASV8 | ASV9 | ASV10 |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| 1 |    16 |     0 |     0 |    0 | 160 |    0 |   0 |   0 | 685 |   0 |\n",
       "| 10 |     0 |   244 |     0 |    0 | 536 |   48 |   0 |   0 |   0 | 162 |\n",
       "| 100 |   251 | 31618 |     0 |    0 |   0 |    0 | 705 |   0 | 396 |   0 |\n",
       "| 101 | 15722 |     0 |  6603 |    0 |   0 |    0 |   0 |   0 |   0 |   0 |\n",
       "| 102 |  1993 |     0 |     0 |    0 |  58 |   39 |   0 |   0 |   0 |   0 |\n",
       "| 103 |    81 |     0 |     0 |    0 |   0 |  169 |   0 |   0 |   0 | 103 |\n",
       "| 104 |   326 |     0 | 18871 |    0 |   0 |    0 |   0 |   0 |   0 |   0 |\n",
       "| 106 |    11 |     0 |   500 |    0 |   0 |    0 |   4 |   0 |   0 |   0 |\n",
       "| 107 |    38 |     0 |     0 |    0 | 343 |    0 |  60 |  76 |   0 |   0 |\n",
       "| 108 |  8064 |   125 |     0 | 1095 | 457 | 1378 | 530 | 239 |   0 | 846 |\n",
       "\n"
      ],
      "text/plain": [
       "    ASV1  ASV2  ASV3  ASV4 ASV5 ASV6 ASV7 ASV8 ASV9 ASV10\n",
       "1      16     0     0    0 160     0   0    0  685    0  \n",
       "10      0   244     0    0 536    48   0    0    0  162  \n",
       "100   251 31618     0    0   0     0 705    0  396    0  \n",
       "101 15722     0  6603    0   0     0   0    0    0    0  \n",
       "102  1993     0     0    0  58    39   0    0    0    0  \n",
       "103    81     0     0    0   0   169   0    0    0  103  \n",
       "104   326     0 18871    0   0     0   0    0    0    0  \n",
       "106    11     0   500    0   0     0   4    0    0    0  \n",
       "107    38     0     0    0 343     0  60   76    0    0  \n",
       "108  8064   125     0 1095 457  1378 530  239    0  846  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "phyloseq::otu_table(e3f.f)[1:10, 1:10]"
   ]
  }
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