docs/source/notebooks/bulk.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a6b025d6",
   "metadata": {},
   "source": [
    "# Bulk functional analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41d9ebac",
   "metadata": {},
   "source": [
    "Bulk RNA-seq yields many molecular readouts that are hard to interpret by themselves. One way of summarizing this information is by inferring pathway and transcription factor activities from prior knowledge.\n",
    "\n",
    "In this notebook we showcase how to use `decoupler` for transcription factor (TF) and pathway activity inference from a human data-set. The data consists of 6 samples of hepatic stellate cells (HSC) where three of them were activated by the cytokine Transforming growth factor (TGF-β), it is available at GEO [here](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE151251).\n",
    "\n",
    "<div class=\"alert alert-info\">\n",
    "\n",
    "**Note**\n",
    "    \n",
    "This tutorial assumes that you already know the basics of `decoupler`. Else, check out the [Usage](https://decoupler-py.readthedocs.io/en/latest/notebooks/usage.html) tutorial first.\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36d324eb",
   "metadata": {},
   "source": [
    "## Loading packages\n",
    "\n",
    "First, we need to load the relevant packages, `scanpy` to handle RNA-seq data\n",
    "and `decoupler` to use statistical methods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "20d55bbb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import scanpy as sc\n",
    "import decoupler as dc\n",
    "\n",
    "# Only needed for processing\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from anndata import AnnData"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47b662e1",
   "metadata": {},
   "source": [
    "## Loading the data\n",
    "\n",
    "We can download the data easily from GEO:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4651c698",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2024-02-19 18:39:54--  https://www.ncbi.nlm.nih.gov/geo/download/?acc=GSE151251&format=file&file=GSE151251%5FHSCs%5FCtrl%2Evs%2EHSCs%5FTGFb%2Ecounts%2Etsv%2Egz\n",
      "Resolving www.ncbi.nlm.nih.gov (www.ncbi.nlm.nih.gov)... 130.14.29.110, 2607:f220:41e:4290::110\n",
      "Connecting to www.ncbi.nlm.nih.gov (www.ncbi.nlm.nih.gov)|130.14.29.110|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 1578642 (1,5M) [application/octet-stream]\n",
      "Saving to: ‘counts.txt.gz’\n",
      "\n",
      "counts.txt.gz       100%[===================>]   1,50M  2,15MB/s    in 0,7s    \n",
      "\n",
      "2024-02-19 18:39:55 (2,15 MB/s) - ‘counts.txt.gz’ saved [1578642/1578642]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!wget 'https://www.ncbi.nlm.nih.gov/geo/download/?acc=GSE151251&format=file&file=GSE151251%5FHSCs%5FCtrl%2Evs%2EHSCs%5FTGFb%2Ecounts%2Etsv%2Egz' -O counts.txt.gz\n",
    "!gzip -d -f counts.txt.gz"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01794f8c",
   "metadata": {},
   "source": [
    "We can then read it using `pandas`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "43f47b5b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>GeneName</th>\n",
       "      <th>DDX11L1</th>\n",
       "      <th>WASH7P</th>\n",
       "      <th>MIR6859-1</th>\n",
       "      <th>MIR1302-11</th>\n",
       "      <th>MIR1302-9</th>\n",
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       "      <th>RP11-34P13.7</th>\n",
       "      <th>...</th>\n",
       "      <th>MT-ND4</th>\n",
       "      <th>MT-TH</th>\n",
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       "      <th>MT-ND5</th>\n",
       "      <th>MT-ND6</th>\n",
       "      <th>MT-TE</th>\n",
       "      <th>MT-CYB</th>\n",
       "      <th>MT-TT</th>\n",
       "      <th>MT-TP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>25_HSCs-Ctrl1</th>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
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       "      <td>476</td>\n",
       "      <td>493</td>\n",
       "      <td>54466</td>\n",
       "      <td>17184</td>\n",
       "      <td>1302</td>\n",
       "      <td>54099</td>\n",
       "      <td>258</td>\n",
       "      <td>475</td>\n",
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       "    <tr>\n",
       "      <th>26_HSCs-Ctrl2</th>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>66</td>\n",
       "      <td>...</td>\n",
       "      <td>114914</td>\n",
       "      <td>355</td>\n",
       "      <td>388</td>\n",
       "      <td>436</td>\n",
       "      <td>64698</td>\n",
       "      <td>21106</td>\n",
       "      <td>1492</td>\n",
       "      <td>62679</td>\n",
       "      <td>253</td>\n",
       "      <td>396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27_HSCs-Ctrl3</th>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>155365</td>\n",
       "      <td>377</td>\n",
       "      <td>438</td>\n",
       "      <td>480</td>\n",
       "      <td>85650</td>\n",
       "      <td>31860</td>\n",
       "      <td>2033</td>\n",
       "      <td>89559</td>\n",
       "      <td>282</td>\n",
       "      <td>448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31_HSCs-TGFb1</th>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>...</td>\n",
       "      <td>110866</td>\n",
       "      <td>373</td>\n",
       "      <td>441</td>\n",
       "      <td>481</td>\n",
       "      <td>60325</td>\n",
       "      <td>19496</td>\n",
       "      <td>1447</td>\n",
       "      <td>66283</td>\n",
       "      <td>172</td>\n",
       "      <td>341</td>\n",
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       "      <th>32_HSCs-TGFb2</th>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
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       "      <td>343</td>\n",
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       "      <td>9054</td>\n",
       "      <td>624</td>\n",
       "      <td>27535</td>\n",
       "      <td>96</td>\n",
       "      <td>216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33_HSCs-TGFb3</th>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
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       "      <td>243</td>\n",
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       "</table>\n",
       "<p>6 rows × 64253 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "GeneName       DDX11L1  WASH7P  MIR6859-1  MIR1302-11  MIR1302-9  FAM138A  \\\n",
       "25_HSCs-Ctrl1        0       9         10           1          0        0   \n",
       "26_HSCs-Ctrl2        0      12         14           0          0        0   \n",
       "27_HSCs-Ctrl3        0      14         10           0          0        0   \n",
       "31_HSCs-TGFb1        0      11         16           0          0        0   \n",
       "32_HSCs-TGFb2        0       5          8           0          0        0   \n",
       "33_HSCs-TGFb3        0      12          5           0          0        0   \n",
       "\n",
       "GeneName       OR4G4P  OR4G11P  OR4F5  RP11-34P13.7  ...  MT-ND4  MT-TH  \\\n",
       "25_HSCs-Ctrl1       0        0      0            33  ...   93192    342   \n",
       "26_HSCs-Ctrl2       0        0      0            66  ...  114914    355   \n",
       "27_HSCs-Ctrl3       0        0      0            52  ...  155365    377   \n",
       "31_HSCs-TGFb1       0        0      0            54  ...  110866    373   \n",
       "32_HSCs-TGFb2       0        0      0            44  ...   45488    239   \n",
       "33_HSCs-TGFb3       0        0      0            32  ...   70704    344   \n",
       "\n",
       "GeneName       MT-TS2  MT-TL2  MT-ND5  MT-ND6  MT-TE  MT-CYB  MT-TT  MT-TP  \n",
       "25_HSCs-Ctrl1     476     493   54466   17184   1302   54099    258    475  \n",
       "26_HSCs-Ctrl2     388     436   64698   21106   1492   62679    253    396  \n",
       "27_HSCs-Ctrl3     438     480   85650   31860   2033   89559    282    448  \n",
       "31_HSCs-TGFb1     441     481   60325   19496   1447   66283    172    341  \n",
       "32_HSCs-TGFb2     331     343   27442    9054    624   27535     96    216  \n",
       "33_HSCs-TGFb3     453     497   45443   13796   1077   43415    192    243  \n",
       "\n",
       "[6 rows x 64253 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read raw data and process it\n",
    "adata = pd.read_csv('counts.txt', index_col=2, sep='\\t').iloc[:, 5:].T\n",
    "adata"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "212f7c7c",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-info\">\n",
    "\n",
    "**Note**\n",
    "    \n",
    "In case your data does not contain gene symbols but rather gene ids like ENSMBL, you can use the function `sc.queries.biomart_annotations` to retrieve them.\n",
    "In this other [vignette](https://decoupler-py.readthedocs.io/en/latest/notebooks/pseudobulk.html), ENSMBL ids are transformed into gene symbols.\n",
    "\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6335a2fe",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-info\">\n",
    "\n",
    "**Note**\n",
    "    \n",
    "In case your data is not from human but rather a model organism, you can find their human orthologs using `pypath`.\n",
    "Check this GitHub [issue](https://github.com/saezlab/decoupler-py/issues/5#issuecomment-1137099265) where mouse genes are transformed into human.\n",
    "\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6bf58d9c",
   "metadata": {},
   "source": [
    "The obtained data consist of raw read counts for six different samples (three controls, three treatments) for ~60k genes.\n",
    "Before continuing, we will transform our expression data into an `AnnData` object. It handles annotated data matrices\n",
    "efficiently in memory and on disk and is used in the scverse framework. You can read more about it \n",
    "[here](https://scverse.org/) and [here](https://anndata.readthedocs.io/en/latest/)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6d5ab0b2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 6 × 64253"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Transform to AnnData object\n",
    "adata = AnnData(adata, dtype=np.float32)\n",
    "adata.var_names_make_unique()\n",
    "adata"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42c4244a",
   "metadata": {},
   "source": [
    "Inside an `AnnData` object, there is the `.obs` attribute where we can store the metadata of our samples.\n",
    "Here we will infer the metadata by processing the sample ids, but this could also be added from a separate dataframe:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "836b0d69",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>condition</th>\n",
       "      <th>sample_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>25_HSCs-Ctrl1</th>\n",
       "      <td>control</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26_HSCs-Ctrl2</th>\n",
       "      <td>control</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27_HSCs-Ctrl3</th>\n",
       "      <td>control</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31_HSCs-TGFb1</th>\n",
       "      <td>treatment</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32_HSCs-TGFb2</th>\n",
       "      <td>treatment</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33_HSCs-TGFb3</th>\n",
       "      <td>treatment</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               condition sample_id\n",
       "25_HSCs-Ctrl1    control        25\n",
       "26_HSCs-Ctrl2    control        26\n",
       "27_HSCs-Ctrl3    control        27\n",
       "31_HSCs-TGFb1  treatment        31\n",
       "32_HSCs-TGFb2  treatment        32\n",
       "33_HSCs-TGFb3  treatment        33"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Process treatment information\n",
    "adata.obs['condition'] = ['control' if '-Ctrl' in sample_id else 'treatment' for sample_id in adata.obs.index]\n",
    "\n",
    "# Process sample information\n",
    "adata.obs['sample_id'] = [sample_id.split('_')[0] for sample_id in adata.obs.index]\n",
    "\n",
    "# Visualize metadata\n",
    "adata.obs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc5f2a9b",
   "metadata": {},
   "source": [
    "## Quality control\n",
    "\n",
    "Before doing anything we need to ensure that our data passes some quality control thresholds. In transcriptomics it can happen\n",
    "that some genes were not properly profiled and thus need to be removed.\n",
    "\n",
    "To filter genes, we will follow the strategy implemented in the function `filterByExpr` from [edgeR](https://rdrr.io/bioc/edgeR/man/filterByExpr.html).\n",
    "It keeps genes that have a minimum total number of reads across samples (`min_total_count`), and that have a minimum number of counts in a number of samples (`min_count`).\n",
    "\n",
    "We can plot how many genes do we keep, you can play with the `min_count` and `min_total_count` to check how many genes would be kept when changed:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3a40896c-568e-4a86-a1b7-a5d1b2cb9e3e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dc.plot_filter_by_expr(adata, group='condition', min_count=10, min_total_count=15, large_n=1, min_prop=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90e9b2ae-403e-4bfe-9471-e16ca3477744",
   "metadata": {},
   "source": [
    "Here we can observe the frequency of genes with different total sum of counts and number of samples. The dashed lines indicate the current thresholds, meaning that only the genes in the upper-right corner are going to be kept. Filtering parameters is completely arbitrary, but a good rule of thumb is to identify bimodal distributions and split them modifying the available thresholds.\n",
    "In this example, with the default values we would keep a good quantity of genes while filtering potential noisy genes.\n",
    "\n",
    "<div class=\"alert alert-info\">\n",
    "\n",
    "**Note**\n",
    "    \n",
    "Changing the value of `min_count` will drastically change the distribution of \"Number of samples\", not change its threshold.\n",
    "In case you want to lower or increase it, you need to play with the `group`, `large_n` and `min_prop` parameters. \n",
    "\n",
    "\n",
    "</div>\n",
    "\n",
    "<div class=\"alert alert-info\">\n",
    "\n",
    "**Note**\n",
    "\n",
    "This thresholds can vary a lot between datasets, manual assessment of them needs to be considered. For example, it might be\n",
    "the case that many genes are not expressed in just one sample which they would get removed by the current setting. For this\n",
    "specific dataset it is fine.\n",
    "\n",
    "</div>\n",
    "\n",
    "Once we are content with the threshold parameters, we can perform the actual filtering:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6c681d17-998f-4319-8eec-b067dbe6a016",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 6 × 19713\n",
       "    obs: 'condition', 'sample_id'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Obtain genes that pass the thresholds\n",
    "genes = dc.filter_by_expr(adata, group='condition', min_count=10, min_total_count=15, large_n=1, min_prop=1)\n",
    "\n",
    "# Filter by these genes\n",
    "adata = adata[:, genes].copy()\n",
    "adata"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4fa8b2a1-7c77-4d66-afbd-cb0559157857",
   "metadata": {},
   "source": [
    "## Differential expression analysis\n",
    "\n",
    "In order to identify which are the genes that are changing the most between treatment and control we can perform differential\n",
    "expression analysis (DEA). For this example, we will perform a simple experimental design where we compare the gene expression\n",
    "of treated cells against controls. We will use the python implementation of the framework DESeq2, but we could have used any\n",
    "other one (`limma` or `edgeR` for example). For a better understanding how it works, check\n",
    "[DESeq2's documentation](https://pydeseq2.readthedocs.io/en/latest/). Note that more complex experimental designs can be used\n",
    "by adding more factors to the `design_factors` argument."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4df3c8ca-e94a-44d9-8ff7-2c51f13e56b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import DESeq2\n",
    "from pydeseq2.dds import DeseqDataSet, DefaultInference\n",
    "from pydeseq2.ds import DeseqStats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b6e6ca8a-97c6-4cfe-8662-1833911b5b64",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Build DESeq2 object\n",
    "inference = DefaultInference(n_cpus=8)\n",
    "dds = DeseqDataSet(\n",
    "    adata=adata,\n",
    "    design_factors='condition',\n",
    "    refit_cooks=True,\n",
    "    inference=inference,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "96cc03ee-f9c2-4e47-9660-642ceecf6e6f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fitting size factors...\n",
      "... done in 0.00 seconds.\n",
      "\n",
      "Fitting dispersions...\n",
      "... done in 40.73 seconds.\n",
      "\n",
      "Fitting dispersion trend curve...\n",
      "... done in 0.79 seconds.\n",
      "\n",
      "Fitting MAP dispersions...\n",
      "... done in 47.51 seconds.\n",
      "\n",
      "Fitting LFCs...\n",
      "... done in 3.20 seconds.\n",
      "\n",
      "Refitting 0 outliers.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Compute LFCs\n",
    "dds.deseq2()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c28301e1-a2ad-411a-a8ab-08e7d65fd43e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Extract contrast between COVID-19 vs normal\n",
    "stat_res = DeseqStats(\n",
    "    dds,\n",
    "    contrast=[\"condition\", 'treatment', 'control'],\n",
    "    inference=inference\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "44a071fb-41ed-4dc4-ab97-89cd11ddc4f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Running Wald tests...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Log2 fold change & Wald test p-value: condition treatment vs control\n",
      "                  baseMean  log2FoldChange     lfcSE      stat    pvalue  \\\n",
      "GeneName                                                                   \n",
      "WASH7P           10.349783       -0.013838  0.588150 -0.023528  0.981229   \n",
      "MIR6859-1        10.114621        0.006602  0.593410  0.011125  0.991123   \n",
      "RP11-34P13.7     45.731312        0.077657  0.297658  0.260893  0.794175   \n",
      "RP11-34P13.8     29.498381       -0.075630  0.250611 -0.301783  0.762818   \n",
      "CICP27          106.032654        0.155742  0.175942  0.885185  0.376057   \n",
      "...                    ...             ...       ...       ...       ...   \n",
      "MT-ND6        17914.984375       -0.435304  0.278967 -1.560414  0.118662   \n",
      "MT-TE          1281.293335       -0.332495  0.287849 -1.155101  0.248049   \n",
      "MT-CYB        54955.449219       -0.313285  0.286940 -1.091813  0.274915   \n",
      "MT-TT           204.692215       -0.483703  0.332233 -1.455916  0.145416   \n",
      "MT-TP           345.049713       -0.462065  0.197978 -2.333926  0.019600   \n",
      "\n",
      "                  padj  \n",
      "GeneName                \n",
      "WASH7P        0.986735  \n",
      "MIR6859-1     0.994048  \n",
      "RP11-34P13.7  0.854935  \n",
      "RP11-34P13.8  0.831118  \n",
      "CICP27        0.494115  \n",
      "...                ...  \n",
      "MT-ND6        0.192431  \n",
      "MT-TE         0.354693  \n",
      "MT-CYB        0.385998  \n",
      "MT-TT         0.228249  \n",
      "MT-TP         0.039889  \n",
      "\n",
      "[19713 rows x 6 columns]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "... done in 1.68 seconds.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Compute Wald test\n",
    "stat_res.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "01376338-4f96-4a3b-8d5f-deb06054e7ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>baseMean</th>\n",
       "      <th>log2FoldChange</th>\n",
       "      <th>lfcSE</th>\n",
       "      <th>stat</th>\n",
       "      <th>pvalue</th>\n",
       "      <th>padj</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GeneName</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>WASH7P</th>\n",
       "      <td>10.349783</td>\n",
       "      <td>-0.013838</td>\n",
       "      <td>0.588150</td>\n",
       "      <td>-0.023528</td>\n",
       "      <td>0.981229</td>\n",
       "      <td>0.986735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIR6859-1</th>\n",
       "      <td>10.114621</td>\n",
       "      <td>0.006602</td>\n",
       "      <td>0.593410</td>\n",
       "      <td>0.011125</td>\n",
       "      <td>0.991123</td>\n",
       "      <td>0.994048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RP11-34P13.7</th>\n",
       "      <td>45.731312</td>\n",
       "      <td>0.077657</td>\n",
       "      <td>0.297658</td>\n",
       "      <td>0.260893</td>\n",
       "      <td>0.794175</td>\n",
       "      <td>0.854935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RP11-34P13.8</th>\n",
       "      <td>29.498381</td>\n",
       "      <td>-0.075630</td>\n",
       "      <td>0.250611</td>\n",
       "      <td>-0.301783</td>\n",
       "      <td>0.762818</td>\n",
       "      <td>0.831118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CICP27</th>\n",
       "      <td>106.032654</td>\n",
       "      <td>0.155742</td>\n",
       "      <td>0.175942</td>\n",
       "      <td>0.885185</td>\n",
       "      <td>0.376057</td>\n",
       "      <td>0.494115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MT-ND6</th>\n",
       "      <td>17914.984375</td>\n",
       "      <td>-0.435304</td>\n",
       "      <td>0.278967</td>\n",
       "      <td>-1.560414</td>\n",
       "      <td>0.118662</td>\n",
       "      <td>0.192431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MT-TE</th>\n",
       "      <td>1281.293335</td>\n",
       "      <td>-0.332495</td>\n",
       "      <td>0.287849</td>\n",
       "      <td>-1.155101</td>\n",
       "      <td>0.248049</td>\n",
       "      <td>0.354693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MT-CYB</th>\n",
       "      <td>54955.449219</td>\n",
       "      <td>-0.313285</td>\n",
       "      <td>0.286940</td>\n",
       "      <td>-1.091813</td>\n",
       "      <td>0.274915</td>\n",
       "      <td>0.385998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MT-TT</th>\n",
       "      <td>204.692215</td>\n",
       "      <td>-0.483703</td>\n",
       "      <td>0.332233</td>\n",
       "      <td>-1.455916</td>\n",
       "      <td>0.145416</td>\n",
       "      <td>0.228249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MT-TP</th>\n",
       "      <td>345.049713</td>\n",
       "      <td>-0.462065</td>\n",
       "      <td>0.197978</td>\n",
       "      <td>-2.333926</td>\n",
       "      <td>0.019600</td>\n",
       "      <td>0.039889</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>19713 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  baseMean  log2FoldChange     lfcSE      stat    pvalue  \\\n",
       "GeneName                                                                   \n",
       "WASH7P           10.349783       -0.013838  0.588150 -0.023528  0.981229   \n",
       "MIR6859-1        10.114621        0.006602  0.593410  0.011125  0.991123   \n",
       "RP11-34P13.7     45.731312        0.077657  0.297658  0.260893  0.794175   \n",
       "RP11-34P13.8     29.498381       -0.075630  0.250611 -0.301783  0.762818   \n",
       "CICP27          106.032654        0.155742  0.175942  0.885185  0.376057   \n",
       "...                    ...             ...       ...       ...       ...   \n",
       "MT-ND6        17914.984375       -0.435304  0.278967 -1.560414  0.118662   \n",
       "MT-TE          1281.293335       -0.332495  0.287849 -1.155101  0.248049   \n",
       "MT-CYB        54955.449219       -0.313285  0.286940 -1.091813  0.274915   \n",
       "MT-TT           204.692215       -0.483703  0.332233 -1.455916  0.145416   \n",
       "MT-TP           345.049713       -0.462065  0.197978 -2.333926  0.019600   \n",
       "\n",
       "                  padj  \n",
       "GeneName                \n",
       "WASH7P        0.986735  \n",
       "MIR6859-1     0.994048  \n",
       "RP11-34P13.7  0.854935  \n",
       "RP11-34P13.8  0.831118  \n",
       "CICP27        0.494115  \n",
       "...                ...  \n",
       "MT-ND6        0.192431  \n",
       "MT-TE         0.354693  \n",
       "MT-CYB        0.385998  \n",
       "MT-TT         0.228249  \n",
       "MT-TP         0.039889  \n",
       "\n",
       "[19713 rows x 6 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract results\n",
    "results_df = stat_res.results_df\n",
    "results_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9e0f1e2-c8a4-4d2e-afaf-d454d4e5b40e",
   "metadata": {},
   "source": [
    "We can plot the obtained results in a volcano plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f0ceebe8-97ad-4447-aef2-8bd63e9f414e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dc.plot_volcano_df(\n",
    "    results_df,\n",
    "    x='log2FoldChange',\n",
    "    y='padj',\n",
    "    top=20,\n",
    "    figsize=(5, 5)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8676b266-dd45-495f-baee-c1c684a5d445",
   "metadata": {},
   "source": [
    "After performing DEA, we can use the obtained gene level statistics to perform enrichment analysis. Any statistic can be used,\n",
    "but we recommend using the t-values instead of logFCs since t-values incorporate the significance of change in their value.\n",
    "We will transform the obtained t-values stored in `stats` to a wide matrix so that it can be used by `decoupler`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "715f76e6-a2a5-46bc-9c11-e4f352c651fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>GeneName</th>\n",
       "      <th>WASH7P</th>\n",
       "      <th>MIR6859-1</th>\n",
       "      <th>RP11-34P13.7</th>\n",
       "      <th>RP11-34P13.8</th>\n",
       "      <th>CICP27</th>\n",
       "      <th>FO538757.2</th>\n",
       "      <th>AP006222.2</th>\n",
       "      <th>RP4-669L17.10</th>\n",
       "      <th>MTND1P23</th>\n",
       "      <th>MTND2P28</th>\n",
       "      <th>...</th>\n",
       "      <th>MT-ND4</th>\n",
       "      <th>MT-TH</th>\n",
       "      <th>MT-TS2</th>\n",
       "      <th>MT-TL2</th>\n",
       "      <th>MT-ND5</th>\n",
       "      <th>MT-ND6</th>\n",
       "      <th>MT-TE</th>\n",
       "      <th>MT-CYB</th>\n",
       "      <th>MT-TT</th>\n",
       "      <th>MT-TP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>treatment.vs.control</th>\n",
       "      <td>-0.023528</td>\n",
       "      <td>0.011125</td>\n",
       "      <td>0.260893</td>\n",
       "      <td>-0.301783</td>\n",
       "      <td>0.885185</td>\n",
       "      <td>-2.193677</td>\n",
       "      <td>2.102634</td>\n",
       "      <td>-0.36349</td>\n",
       "      <td>-1.328259</td>\n",
       "      <td>-0.498827</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.435491</td>\n",
       "      <td>0.747514</td>\n",
       "      <td>0.752503</td>\n",
       "      <td>0.777125</td>\n",
       "      <td>-1.243008</td>\n",
       "      <td>-1.560414</td>\n",
       "      <td>-1.155101</td>\n",
       "      <td>-1.091813</td>\n",
       "      <td>-1.455916</td>\n",
       "      <td>-2.333926</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 19713 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "GeneName                WASH7P  MIR6859-1  RP11-34P13.7  RP11-34P13.8  \\\n",
       "treatment.vs.control -0.023528   0.011125      0.260893     -0.301783   \n",
       "\n",
       "GeneName                CICP27  FO538757.2  AP006222.2  RP4-669L17.10  \\\n",
       "treatment.vs.control  0.885185   -2.193677    2.102634       -0.36349   \n",
       "\n",
       "GeneName              MTND1P23  MTND2P28  ...    MT-ND4     MT-TH    MT-TS2  \\\n",
       "treatment.vs.control -1.328259 -0.498827  ... -1.435491  0.747514  0.752503   \n",
       "\n",
       "GeneName                MT-TL2    MT-ND5    MT-ND6     MT-TE    MT-CYB  \\\n",
       "treatment.vs.control  0.777125 -1.243008 -1.560414 -1.155101 -1.091813   \n",
       "\n",
       "GeneName                 MT-TT     MT-TP  \n",
       "treatment.vs.control -1.455916 -2.333926  \n",
       "\n",
       "[1 rows x 19713 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mat = results_df[['stat']].T.rename(index={'stat': 'treatment.vs.control'})\n",
    "mat"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3fe9dee7",
   "metadata": {},
   "source": [
    "## Transcription factor activity inference\n",
    "\n",
    "The first functional analysis we can perform is to infer transcription factor (TF) activities from our transcriptomics data. We will need a gene regulatory network (GRN) and a statistical method.\n",
    "\n",
    "### CollecTRI network\n",
    "[CollecTRI](https://github.com/saezlab/CollecTRI) is a comprehensive resource\n",
    "containing a curated collection of TFs and their transcriptional targets\n",
    "compiled from 12 different resources. This collection provides an increased\n",
    "coverage of transcription factors and a superior performance in identifying\n",
    "perturbed TFs compared to our previous\n",
    "[DoRothEA](https://saezlab.github.io/dorothea/) network and other literature\n",
    "based GRNs. Similar to DoRothEA, interactions are weighted by their mode of\n",
    "regulation (activation or inhibition).\n",
    "\n",
    "For this example we will use the human version (mouse and rat are also\n",
    "available). We can use `decoupler` to retrieve it from `omnipath`. The argument\n",
    "`split_complexes` keeps complexes or splits them into subunits, by default we\n",
    "recommend to keep complexes together.\n",
    "\n",
    "<div class=\"alert alert-info\">\n",
    "\n",
    "**Note**\n",
    "\n",
    "In this tutorial we use the network CollecTRI, but we could use any other GRN coming from an inference method such as [CellOracle](https://morris-lab.github.io/CellOracle.documentation/), [pySCENIC](https://pyscenic.readthedocs.io/en/latest/) or [SCENIC+](https://scenicplus.readthedocs.io/en/latest/). \n",
    "\n",
    "</div> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3b8386a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>source</th>\n",
       "      <th>target</th>\n",
       "      <th>weight</th>\n",
       "      <th>PMID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MYC</td>\n",
       "      <td>TERT</td>\n",
       "      <td>1</td>\n",
       "      <td>10022128;10491298;10606235;10637317;10723141;1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>BGLAP</td>\n",
       "      <td>1</td>\n",
       "      <td>10022617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SMAD3</td>\n",
       "      <td>JUN</td>\n",
       "      <td>1</td>\n",
       "      <td>10022869;12374795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SMAD4</td>\n",
       "      <td>JUN</td>\n",
       "      <td>1</td>\n",
       "      <td>10022869;12374795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>STAT5A</td>\n",
       "      <td>IL2</td>\n",
       "      <td>1</td>\n",
       "      <td>10022878;11435608;17182565;17911616;22854263;2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43173</th>\n",
       "      <td>NFKB</td>\n",
       "      <td>hsa-miR-143-3p</td>\n",
       "      <td>1</td>\n",
       "      <td>19472311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43174</th>\n",
       "      <td>AP1</td>\n",
       "      <td>hsa-miR-206</td>\n",
       "      <td>1</td>\n",
       "      <td>19721712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43175</th>\n",
       "      <td>NFKB</td>\n",
       "      <td>hsa-miR-21-5p</td>\n",
       "      <td>1</td>\n",
       "      <td>20813833;22387281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43176</th>\n",
       "      <td>NFKB</td>\n",
       "      <td>hsa-miR-224-5p</td>\n",
       "      <td>1</td>\n",
       "      <td>23474441;23988648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43177</th>\n",
       "      <td>AP1</td>\n",
       "      <td>hsa-miR-144</td>\n",
       "      <td>1</td>\n",
       "      <td>23546882</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>43178 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       source          target  weight  \\\n",
       "0         MYC            TERT       1   \n",
       "1        SPI1           BGLAP       1   \n",
       "2       SMAD3             JUN       1   \n",
       "3       SMAD4             JUN       1   \n",
       "4      STAT5A             IL2       1   \n",
       "...       ...             ...     ...   \n",
       "43173    NFKB  hsa-miR-143-3p       1   \n",
       "43174     AP1     hsa-miR-206       1   \n",
       "43175    NFKB   hsa-miR-21-5p       1   \n",
       "43176    NFKB  hsa-miR-224-5p       1   \n",
       "43177     AP1     hsa-miR-144       1   \n",
       "\n",
       "                                                    PMID  \n",
       "0      10022128;10491298;10606235;10637317;10723141;1...  \n",
       "1                                               10022617  \n",
       "2                                      10022869;12374795  \n",
       "3                                      10022869;12374795  \n",
       "4      10022878;11435608;17182565;17911616;22854263;2...  \n",
       "...                                                  ...  \n",
       "43173                                           19472311  \n",
       "43174                                           19721712  \n",
       "43175                                  20813833;22387281  \n",
       "43176                                  23474441;23988648  \n",
       "43177                                           23546882  \n",
       "\n",
       "[43178 rows x 4 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Retrieve CollecTRI gene regulatory network\n",
    "collectri = dc.get_collectri(organism='human', split_complexes=False)\n",
    "collectri"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bfb8c1d-3709-471a-804f-71a261bb9f97",
   "metadata": {},
   "source": [
    "### Activity inference with Univariate Linear Model (ULM)\n",
    "\n",
    "To infer TF enrichment scores we will run the Univariate Linear Model (`ulm`) method. For each sample in our dataset (`mat`) and each TF in our network (`net`), it fits a linear model that predicts the observed gene expression\n",
    "based solely on the TF's TF-Gene interaction weights. Once fitted, the obtained t-value of the slope is the score. If it is positive, we interpret that the TF is active and if it is negative we interpret that it is inactive.\n",
    "\n",
    "<img src=\"../ulm.png\" />\n",
    "\n",
    "We can run `ulm` with a one-liner:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e46d54de-e219-4d5d-8ccf-f3eb3619c204",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running ulm on mat with 1 samples and 19713 targets for 655 sources.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ABL1</th>\n",
       "      <th>AHR</th>\n",
       "      <th>AIRE</th>\n",
       "      <th>AP1</th>\n",
       "      <th>APEX1</th>\n",
       "      <th>AR</th>\n",
       "      <th>ARID1A</th>\n",
       "      <th>ARID3A</th>\n",
       "      <th>ARID3B</th>\n",
       "      <th>ARID4A</th>\n",
       "      <th>...</th>\n",
       "      <th>ZNF362</th>\n",
       "      <th>ZNF382</th>\n",
       "      <th>ZNF384</th>\n",
       "      <th>ZNF395</th>\n",
       "      <th>ZNF436</th>\n",
       "      <th>ZNF699</th>\n",
       "      <th>ZNF76</th>\n",
       "      <th>ZNF804A</th>\n",
       "      <th>ZNF91</th>\n",
       "      <th>ZXDC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>treatment.vs.control</th>\n",
       "      <td>-1.660472</td>\n",
       "      <td>-1.518117</td>\n",
       "      <td>-1.422092</td>\n",
       "      <td>-2.579365</td>\n",
       "      <td>-2.427458</td>\n",
       "      <td>-0.039337</td>\n",
       "      <td>-6.223142</td>\n",
       "      <td>1.033265</td>\n",
       "      <td>2.227805</td>\n",
       "      <td>-0.615537</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.033799</td>\n",
       "      <td>2.490092</td>\n",
       "      <td>1.336223</td>\n",
       "      <td>-1.069932</td>\n",
       "      <td>-1.448839</td>\n",
       "      <td>-1.049743</td>\n",
       "      <td>0.46968</td>\n",
       "      <td>2.809017</td>\n",
       "      <td>0.559583</td>\n",
       "      <td>-2.681535</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 655 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          ABL1       AHR      AIRE       AP1     APEX1  \\\n",
       "treatment.vs.control -1.660472 -1.518117 -1.422092 -2.579365 -2.427458   \n",
       "\n",
       "                            AR    ARID1A    ARID3A    ARID3B    ARID4A  ...  \\\n",
       "treatment.vs.control -0.039337 -6.223142  1.033265  2.227805 -0.615537  ...   \n",
       "\n",
       "                        ZNF362    ZNF382    ZNF384    ZNF395    ZNF436  \\\n",
       "treatment.vs.control -0.033799  2.490092  1.336223 -1.069932 -1.448839   \n",
       "\n",
       "                        ZNF699    ZNF76   ZNF804A     ZNF91      ZXDC  \n",
       "treatment.vs.control -1.049743  0.46968  2.809017  0.559583 -2.681535  \n",
       "\n",
       "[1 rows x 655 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Infer TF activities with ulm\n",
    "tf_acts, tf_pvals = dc.run_ulm(mat=mat, net=collectri, verbose=True)\n",
    "tf_acts"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3834731",
   "metadata": {},
   "source": [
    "Let us plot the obtained scores for the top active/inactive transcription factors:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f810e11d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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8331MsLbKtikpKbhy5Qp+//13pY6jLpr/MBUhRGvZ2NiIPTYobRKWnZ2N2bNnY9euXTAwMGi0sVFikGaG0q+RxqbKlHTZ2dliT7tIm3VevnwZT548Qa9evdh1FRUVOHv2LDZs2ICSkhJwOByljg+g4EkI0WCyPCo4bNgwXL9+XWzdpEmT4OLigoULF6okcAIUPAkhClJ3SjpjY2OxbGsAYGRkBAsLC4n1ykTBs5lbuPWNuoegdjHTWqh7CKQZouBJCFGIJpbhqM4DrEoUPAkhCmF0lJ/5nWkCzwE1gSESQojmkTl4xsfHw9jYWOx1yKKiIujq6sLDw0OsrVAoBMMw8Pf3h4+Pj9h3J06cAMMwWL58udj65cuXw9bWVubSGiEhIexnXV1dODg4YMGCBXj79q1YvytXroS7uzsMDQ1hZmYm6+ESQmREWZXq4enpiaKiIqSnp7PrUlNTwefzcfHiRbGgdfr0adja2sLLywvnzp0TC7inT5+GjY2NxDWJ06dPw9PTU+bSGgDYkh1//fUX4uLisGXLFolMTaWlpfD390dYWJjMfymEEFIfmYOns7MzrKysxIKeUCjEmDFj4ODggAsXLoit9/T0lBpwhUIhFi1aJBZw3759i4sXL8LT0xM8Hg98Pp9dapbWqF6qVReTs7GxwdixY+Hl5YVffvlFbNwrVqzAf//7X3Tr1q3BfzmEEBno6Khm0XANGqGnpydOnz7Nfj59+jQ8PDwwZMgQdv2bN2/YQNixY0dYW1uz3xUWFuLKlSvw9/eHvb09zp8/DwBIS0tDSUkJPD095T6QzMxMpKWlQU9PT+4+qlEZDkJIfRocPKtPwwsLC3H16lUMGTIEgwcPZmek58+fFwuEnp6e7Hepqano2LEjWrduLbaNUCiEg4MD7OzsGjT448ePg8fjwcDAAN26dcOTJ08wf/78BvUhDZXhIER29d2jkHfRdA0Knh4eHiguLsbvv/8uFgiHDBnCnoYLhUI4OjrC1taW3ebcuXMoKyuDUChkby4NGTJELHjKM+v09PRERkYGLl68iODgYEyaNAl+fn4N7uddVIaDEFKfBgVPJycntGvXDqdPn8bp06fZUsLW1tawsbFBWloaTp8+jaFDh7LbeHp6sgG35jbVAffFixe4ePGi2DayMjIygpOTE3r06IGEhARcvHhRKbWNqAwHIbLTtDIcjaXBI6w+Da85iwSAwYMH48cff8SlS5fEZpHt27eHjY0Njh49ioyMDDZ4tm3bFm3btsXatWtRWlqq0PVOANDR0cHixYuxZMkSvHlDryQS0ljoUSUZeXp64rfffhMLhEDVTHLLli1SA6Gnpyc2bdoEJycntGnTRmyb9evXszeWFOXv7w8Oh4ONGzey6x48eMCW3KioqGDLcRQVFSm8P0KI9pIreL5580ZqICwsLGQfaXp3m8LCQomH6au3UXTWWY3L5WLWrFlYvXo1W1xu2bJl6NmzJyIiIlBUVMSW46j5+BQhRAGMCh5TagLvZzIiqk9Rr4KCApiamiI/P7/JXf+krEqUVUlWDf13Xt3+7/BgGBso/ohgTYVvS+EQtV2jf3OUGKSZo8BBVE4V1yib4zVPQgghNPMkhCiIYXTAKPkapbL7UwXNHyEhhGggmnlqkc8TStQ9BLVYOVmy4iJRIh1G+dcom8A1TwqehBCFaGIZjsag+SMkhBANpJHB8+nTpwgLC4OtrS2bs9Pb2xvnzp0DANjb22PdunVse5FIhM8++wwmJiZsspF327z7mRCiHNr6eqZGnrb7+fmhtLQU27dvh6OjIx4/foyTJ0/i+fPnEm0rKioQGhqK48eP4/Tp0+jdu7caRkwI0TYaFzxfvXqF1NRUCIVC9t15Ozs79OvXT6JtSUkJAgICkJ6ejtTUVDg7Ozf2cAkhDKP81ymbQD5PjQuePB4PPB4Phw8fxr/+9S/o60u/U1pUVARfX188fPgQ586dU2rC4pKSEpSU/O/ONGWSJ4S8S+OueXK5XCQlJWH79u0wMzPDgAEDsHjxYly7dk2s3RdffIGMjAykpqYqPdM7ZZInRHbaes1T44InUHXNMycnB0ePHoWPjw+EQiF69eqFpKQkts2IESNQXFyMVatWKX3/lEmeEFIfjQyeAGBgYIDhw4dj6dKlSEtLQ0hIiFhZ4WHDhuHIkSOIj4/H7NmzlbpvyiRPSANQ9UzN1rlzZzZHZ7URI0bg2LFj+Pbbb/Hpp5+qaWSEaDdtLQCncTeMnj9/Dn9/f0yePBndu3eHsbEx0tPTsXr1aowZM0aivZeXF44fP47Ro0ejsrISGzZsqLXvR48eISMjQ2ydnZ0dzM3NlX0YhJBmTuOCJ4/Hg5ubG+Li4nDv3j2UlZXBxsYGoaGhWLx4sdRthg4diu+//x7vvfceRCJRrQE0NjYWsbGxYuu+++47BAUFKf04CNEajApOs5tAViWNC576+vqIiopCVFRUrW3u378vsc7Dw0OsLtG7baRtQwgh8tK44EkIaVpU8WhRU3hUiYKnFqHUbIQoDwVPQohiGBVUu2wC1zw1f4SEEKKBaOapZZZtL1X3EBpdZLByy+KSd1AmeUIIaTgqAEcIIURmNPMkhChGS0/blTbzDAkJAcMwiI6OFlt/+PBh9j1VoVAo9u5q69atMWrUKFy/fl1sm7Nnz2L06NGwtrYGwzA4fPiwxP48PDwwZ84cifVJSUkwMzOTOsZz586By+XC1dVVnkMkhBCWUk/bDQwMEBMTg5cvX9bZ7vbt28jNzcVPP/2EkpIS+Pr6orT0fzcyiouL0aNHD2zcuFFpY3v16hU+/vhjDBs2TGl9EkL+Vz1T2YumU+oIvby8wOfz63y1EgAsLS3B5/PRq1cvzJkzB9nZ2bh16xb7/ciRI/Hll19i3LhxShvbjBkz8NFHH6F///5K65MQor2UGjw5HA5WrVqF9evX4+HDh/W2z8/PR0pKCgBAT091j5MkJibir7/+EssHWpeSkhIUFBSILYSQWjCMahYNp/QbRuPGjYOrqysiIiIgEAiktmnXrh0AsPk533//fbi4uDR4X5s2bcK2bdvE1pWXl8PAwID9fOfOHSxatAipqangcmU73KioKKxYsaLB4yGEaA+VXFiIiYnB9u3bcfPmTanfp6am4vLly0hKSkLHjh0RHx8v134CAwORkZEhtkRGRrLfV1RU4KOPPsKKFSvQsWNHmfulMhyENIAOo4JM8lo48wSAwYMHw9vbG+Hh4QgJCZH43sHBAWZmZnB2dsaTJ08wfvx4nD17tsH7MTU1hZOTk9g6S0tL9s+FhYVIT0/H1atXMWvWLABAZWUlRCIRuFwufv75ZwwdOlSiX319/VqrdhJC3qGK0+wmcNquslta0dHROHbsGM6fP19nu5kzZyIzMxOHDh1S+hhMTExw/fp1sZnpjBkz4OzsjIyMDLi5uSl9n4QQ7aCyh+S7deuGwMBAfPPNN3W2MzQ0RGhoKCIiIjB27FgwDIOioiLcvXuXbfP3338jIyMDLVu2hK2trcxj0NHRQdeuXcXWWVpawsDAQGI9IUQ+qni0SOseVXpXZGQkKisr6203a9Ys3Lx5E/v27QMApKeno2fPnujZsycAYO7cuejZsyeWLVumyuESQojMGJFIJFL3IDRdQUEBTE1NkZ+f3+TLEFNWJVKbhv47r26ft3UpTFoY1Nu+QWN58xb8aV9o9G+O3m3XMhRICFEOCp6EEMUwKkgMos132wkhpDmjmSchRCHamgyZgqcW0rabRnSdV8UonychhBBZ0cyTEKIYKj2sHiEhIRg7dqzYuv3798PAwABr166V+n1N9vb2YtnpGYZhsza9ePECn3zyCZydndGiRQvY2tri008/RX5+vgqPiBCiDdQePN+1bds2BAYGYvPmzZg3b55M20RGRiI3N5ddrl69CgDIyclBTk4OYmNjkZmZiaSkJJw4cQJTpkxR5SEQol0on6f6rV69GhEREUhJSWlQFnljY2Pw+XyJ9V27dsWBAwfYz+3bt8fKlSsRFBSE8vJymfN7EkLIuzQmeixcuBCbNm3C8ePHVVpnqPp1r7oCZ0lJCUpKStjPlEmekDpU5+BUdp8aTiNG+OOPP2L16tU4cuSIXIFz4cKF4PF47FJbJqdnz57hiy++wLRp0+rsLyoqCqampuxiY2PT4DERQpo3jZh5du/eHc+ePUNERAT69esHHo/XoO3nz58vlnS5VatWEm0KCgrg6+uLzp07Y/ny5XX2Fx4ejrlz54ptSwGUkFpo6d12jQiebdu2xf79++Hp6QkfHx/8+OOPMDY2lnn7Vq1aSWSUr6mwsBA+Pj4wNjbGoUOHoKurW2d/lEmekAagh+TVy87ODmfOnEFeXh58fHxQWFiolH4LCgowYsQI6Onp4ejRo2LF4QghRF4aMfOsZmNjA6FQCE9PT3h7e+PEiRMAqm7yZGRkiLW1sLCo91S6OnC+fv0aO3fuFCsj3Lp1a3A4HJUcByFahWFUcNqu+TNPjQqeQFVZ4poB1MrKCkKhkM0qX23KlCkSZYffdeXKFVy8eBEAJE7r//77b9jb2yt17IQQ7aH24JmUlCSxrm3btsjKypJp+/v379f6nYeHByhRPiEqRtUzCSGEyErtM0/S+ChFG1EqDXhIPioqCgcPHsStW7fQokULuLu7IyYmBs7OzsodVw008ySENHlnzpzBzJkzceHCBfzyyy8oKyvDiBEjUFxcrLJ90syTEKIYDbjmWf1kTrWkpCRYWlri8uXLGDx4sDJHxqLgqYUokzxp7qrTTrZs2VJl+6DgSQhRjApfz3w3KY8sb/9VVlZizpw5GDBgALp27arccdVA1zwJIYphdP5300hZy/8HTxsbG7EkPVFRUfUOZ+bMmcjMzERKSopKD5tmnoQQjZWdnQ0TExP2c32zzlmzZuH48eM4e/YsW1FCVTRu5lmz7EZISAhbWkNXVxcODg5YsGAB3r59K7bNu2U4GIbBwIEDAVQ9RD9lyhQ4ODigRYsWaN++PSIiIlBaql3X/QhRGRVmkjcxMRFbagueIpEIs2bNwqFDh3Dq1Ck4ODio/LA1fubp4+ODxMRElJWV4fLlywgODgbDMIiJiRFrl5iYCB8fH/aznl7VTYJbt26hsrISW7ZsgZOTEzIzMxEaGori4mLExsY26rEQQlRj5syZSE5OxpEjR2BsbIy8vDwAgKmpKVq0aKGSfWp88NTX12dLbNjY2MDLywu//PKLRPA0MzOTWorDx8dHLKg6Ojri9u3b2Lx5MwVPQpRBA/J5bt68GUDVK9k1JSYmiuX6VSaND541ZWZmIi0tDXZ2dgr1k5+fX+cjDFSGg5CmRR05LDTumue7jh8/Dh6PBwMDA3Tr1g1PnjzB/PnzJdoFBASIleI4fPiw1P7u3r2L9evXY/r06bXuk8pwENIAVD1TM3l6emLz5s0oLi5GXFwcuFwu/Pz8JNrFxcXBy8uL/WxlZSXR5tGjR/Dx8YG/vz9CQ0Nr3SeV4SCE1Efjg6eRkRGbizMhIQE9evSAQCCQqL3O5/PrLMWRk5MDT09PuLu7Y+vWrXXuk8pwENIAGpAYRB00f4Q16OjoYPHixViyZAnevHkj83aPHj2Ch4cHevfujcTEROg0gf8whDQVIoZRyaLpmlwU8ff3B4fDwcaNG2VqXx04bW1tERsbi6dPnyIvL499lIEQQuSh8aft7+JyuZg1axZWr16NsLAwGBkZ1dn+l19+wd27d3H37l2JNw4oyzwhSqClNYwYEUWQehUUFMDU1BT5+flir4o1VZRViUjT0H/n1e3zjm2FiZGhcsdS/Br80dM0+jfX5GaeRHEUTIhSacBD8uqg+SMkhBANRDNPQohCVHF3nO62E0JIM0UzTy0UsaNM3UNoVCs+1lX3EJo3Lb3mScGTEKIYDSgApw6aH94JIUQDaVzwfPr0KcLCwmBra8vm8vT29sa5c+cAAPb29my2eCMjI/Tq1Qv79u1jt1++fDlcXV3Zzzdu3ICfnx+73bp16xr5iAhp5pRdv0gV78qrgMaN0M/PD1evXsX27duRlZWFo0ePwsPDA8+fP2fbREZGIjc3F1evXkXfvn0xfvx4pKWlSe3v9evXcHR0RHR0tNRkyYQQIg+Nuub56tUrpKamQigUYsiQIQAAOzs79OvXT6ydsbEx+Hw++Hw+Nm7ciJ07d+LYsWNwd3eX6LNv377o27cvAGDRokWqPwhCtAw9qqQBaiYyrpnJvS5cLhe6urpKLehWUlKCgoICsYUQQmrSqODJ5XKRlJSE7du3w8zMDAMGDMDixYtx7do1qe1LS0sRFRWF/Px8DB06VGnjoEzyhDRA9aNKyl40nMaN0M/PDzk5OTh69Ch8fHwgFArRq1cvJCUlsW0WLlwIHo8HQ0NDxMTEIDo6Gr6+vkobQ3h4OPLz89klOztbaX0TQpoHjbrmWc3AwADDhw/H8OHDsXTpUkydOhURERFsFbz58+cjJCQEPB4Pbdq0AaPk6yOUSZ4Q2YkYHYiUPFNUdn+qoPkjBNC5c2cUFxezn1u1agUnJyfw+XylB05CSANRATj1e/78Ofz9/TF58mR0794dxsbGSE9Px+rVqzFmzBi5+iwtLcWff/7J/vnRo0fIyMgAj8ers+YRIYTURaOCJ4/Hg5ubG+Li4nDv3j2UlZXBxsYGoaGhWLx4sVx95uTkoGfPnuzn2NhYxMbGYsiQIRAKhUoaOSHaSwQVnLY3gZNiyiQvg+aWSZ4SgxBp5M0k//DkXpjwlJxJvug12g37UKN/cxo18ySENEFamhiEgqcWopkYIYqj4EkIUYyWVs/U/KuyhBCigWjmqeW+2F2u7iGo3NIA+meuStqaGIT+VRFCFKOlZTg0f4SEEKKBaOZJCFGICAxEUPJpu5L7UwW5Z54hISFgGAbR0dFi6w8fPsy+by4UCtmSGTWXJUuW1Pk9wzDIy8sDAHz77bcYNGgQzM3NYW5uDi8vL1y6dElsnx4eHpgzZ47Ucd6/fx9TpkyBg4MDWrRogfbt2yMiIkKp+T8JIdpHoZmngYEBYmJiMH36dJibm9fa7vbt22JvCfB4vDq/BwBLS0sAVQE2ICAA7u7u7P5GjBiBGzduoG3btvWO8datW6isrMSWLVvg5OSEzMxMhIaGori4GLGxsQ05XEKIFNqaVUmh4Onl5YW7d+8iKioKq1evrrWdpaUlzMzM5Pp+165dYp+3bduGAwcO4OTJk/j444/rHaOPjw98fHzYz46Ojrh9+zY2b95MwZMQIjeFwjuHw8GqVauwfv16PHz4UFljqtPr169RVlaGli1byt1Hfn5+ndtTGQ5CGoAyyctn3LhxcHV1RURERK1t2rVrx9Yn4vF4YpUwpX3fpUuXWvtauHAhrK2t4eXlJdd47969i/Xr12P69Om1tqEyHISQ+ijlbntMTAyGDh2Kzz77TOr3qampMDY2Zj+/e3303e91daW/ex0dHY2UlBQIhUIYGBg0eJyPHj2Cj48P/P39ERoaWmu78PBwzJ07l/1cUFBAAZSQWtBD8goYPHgwvL29ER4ezpbKqMnBwaHOa571fQ9U5eGMjo7Gr7/+iu7duzd4jDk5OfD09IS7uzu2bt1aZ1sqw0GI7OiGkYKio6Ph6uoKZ2dnZXXJWr16NVauXImffvoJffr0afD2jx49gqenJ3r37o3ExETo6Gj+fxhCiGZTWvDs1q0bAgMD8c033zR42ydPnuDt27di6ywsLKCrq4uYmBgsW7YMycnJsLe3Z5//rL4+Wu3p06fIyMgQ68PKygrl5eXw8PCAnZ0dYmNj8fTpU/Z7Pp/f4LESQt5B+TwVFxkZiT179jR4O2mz1fPnz+Nf//oXNm/ejNLSUnzwwQdi30dERGD58uXs5+TkZCQnJ4u1+eKLL9CuXTvcvXsXd+/eRbt27cS+pyT6hBB5URkOGTS3Mhw1UVYlUk3eMhx/n/8ZxjwjpY6lsKgYDv1HaPRvjv5VaTkKLITIh345hBCFUGIQQgghMqOZJyFEIfScJ9FqUXsr1D0ElQn/kKPuITRvDFTwqJJyu1MFzQ/vhBCigWjmSQhRiAg6ECl5Hqbs/lRBqSOUJ7t869atMWrUKFy/fr3WfqOjo8EwTK3Z4qOiosDhcLBmzRqJ73777TcMGDAAFhYWaNGiBVxcXBAXFyf/QRJCCFRw2l6d7f3ly5d1trt9+zZyc3Px008/oaSkBL6+vlJLY/z+++/YsmVLnclAEhISsGDBAiQkJEh8Z2RkhFmzZuHs2bO4efMmlixZgiVLltSbHIQQIpvqrErKXjSd0oOnl5cX+Hw+oqKi6mxnaWkJPp+PXr16Yc6cOcjOzsatW7fE2hQVFSEwMBDffvttrWU+zpw5gzdv3iAyMhIFBQVIS0sT+75nz54ICAhAly5dYG9vj6CgIHh7eyM1NVWxAyWEaDWlB8+GZpfPz89HSkoKAEBPT0/su5kzZ8LX17fOxMcCgQABAQHQ1dVFQEAABAJBnfu7evUq0tLSMGTIkFrbUCZ5QmRX/aiSshdNp5IRNiS7vJmZGZKTk/H+++/DxcWF/T4lJQVXrlypcwZbUFCA/fv3IygoCAAQFBSEvXv3oqioSOr+9PX10adPH8ycORNTp06ttV/KJE8IqY/KwntMTAy2b9+OmzdvSv0+NTUVly9fRlJSEjp27Ij4+Hj2u+zsbMyePRu7du2qM2P87t270b59e/To0QMA4OrqCjs7O6mZnVJTU5Geno74+HisW7cOu3fvrrXf8PBw5Ofns0t2drash02I1ql+PVPZi6ZT2aNKsmaXd3Z2xpMnTzB+/HicPXsWAHD58mU8efIEvXr1YttXVFTg7Nmz2LBhA0pKSsDhcCAQCHDjxg1wuf87jMrKSiQkJGDKlCkS+wOq8o4+fvwYy5cvR0BAgNSxUyZ5QmRHbxipgKzZ5WfOnImoqCgcOnQI48aNw7BhwyQeXZo0aRJcXFywcOFCcDgcXL9+Henp6RAKhWKVMF+8eAEPDw/cunVL7DJATZWVlSgpKVH8AAkhWkulwVPW7PKGhoYIDQ1FREQExo4dC2NjY3Tt2lWsjZGRESwsLNj1AoEA/fr1w+DBgyX669u3LwQCAdasWYONGzfC1taWDaRnz55FbGwsPv30UyUdJSHaTVsLwKl8bhwZGYnKysp6282aNQs3b97Evn376m1bWlqKnTt3ws/PT+r3fn5+2LFjB8rKylBZWYnw8HC4urqiT58+2LhxI2JiYhAZGdngYyGEkGqUSV4GzTmTfDVKDELkzST/5+XzMK5RT0wZCouK0Ll3f43+zWn+VVlCCNFAlBiEAKDZGZGftt5t1/wREkKIBqKZJyFEIdpaw4iCJwFAN4wIaSgKnoQQhYiggmueTeCKIgVPQohCtPW0XfPDOyGEyGjjxo2wt7eHgYEB3NzccOnSJZXtSyOCZ15eHj755BM4OjpCX18fNjY2GD16NE6ePAkAsLe3x7p169j21Z/fLekhbREKhQCAhw8fQk9PT+K1T0KIYqpez1R2Ps+Gzzz37NmDuXPnIiIiAleuXEGPHj3g7e2NJ0+eqOCoNSB43r9/H71798apU6ewZs0aXL9+HSdOnICnpydmzpxZ57bu7u7Izc1llw8//BA+Pj5i69zd3QEASUlJ+PDDD1FQUICLFy82xqERQhrRV199hdDQUEyaNAmdO3dGfHw8DA0NpZbnUQa1X/P8z3/+A4ZhcOnSJRgZGbHru3TpgsmTJ9e5rZ6eHvh8Pvu5RYsWKCkpEVsHACKRCImJidi0aRPatWsHgUAANzc35R4IIVpKE655lpaW4vLlywgPD2fX6ejowMvLC+fPn1fq2KqpNXi+ePECJ06cwMqVK8UCZzUzMzOl7Of06dN4/fo1vLy80LZtW7i7uyMuLk7qPoGqMhw1U9ZRGQ5C1OPd315tuXafPXuGiooKtGnTRmx9mzZtJGqjKYtaT9vv3r0LkUhUa95NZREIBJgwYQI4HA66du0KR0fHOrM3URkOQmSnyuqZNjY2Yr/F+gpLNia1Bs/GSOj06tUrHDx4kK1zBFTVOqqrUByV4SBEM2RnZ4v9FmueltfUqlUrcDgcPH78WGz948ePJS7jKYtaT9s7dOgAhmFUNq0GgOTkZLx9+1bsGqdIJEJlZSWysrLQsWNHiW2oDAchshOJGIhESr7m+f/9mZiYyJSSTk9PD71798bJkycxduxYAFUVI06ePIlZs2YpdWzV1DrzbNmyJby9vbFx40YUFxdLfP/q1SuF9yEQCDBv3jxkZGSwyx9//IFBgwap7C4cIdpFp+otIyUu8oSmuXPn4ttvv2ULT4aFhaG4uBiTJk1S/iFDAx5V2rhxIyoqKtCvXz8cOHAAd+7cwc2bN/HNN9+gf//+CvWdkZGBK1euYOrUqejatavYEhAQgO3bt6O8vFxJR0IIUafx48cjNjYWy5Ytg6urKzIyMnDixAmJm0jKovbg6ejoiCtXrsDT0xPz5s1D165dMXz4cJw8eRKbN29WqG+BQIDOnTtLvSE1btw4PHnyBD/88INC+yBE22lS6eFZs2bhn3/+QUlJCS5evKjSRxKpDIcMqAxH00ZZlWQjbxmOy1czwTM2VupYigoL0btnV43+zan9IXmiGSjAEHlpwkPy6qD203ZCCGmKaOZJCFEIzTwJIYTIjGaeRKqvjjSf+4hzx2j+LKYp09aZJwVPQohCVPmGkSaj03ZCCJGDWoJnSEgIGIZBdHS02PrDhw+D+f9sKrVliV+yZInY9zVf4czJyUG3bt0wePBg5OfnS/TRokULdOnSBVu3bm20YyWkudOkh+Qbk9pO2w0MDBATE4Pp06fD3Ny81na3b98We0iWx+NJbXfv3j0MHz4cnTt3xr59+9CiRQuJPt68eYNjx44hLCwM7du3x7Bhw5R3QIQQraK203YvLy/w+fx68/NZWlqCz+ezi7Tgee3aNQwcOBD9+/fH4cOHxQJnzT4cHBzw6aefwsHBAVeuXFHq8RCirbR15qm24MnhcLBq1SqsX78eDx8+lLuftLQ0DBkyBH5+fti5cye43Non0yKRCCdOnMCDBw/qfOe1pKQEBQUFYgshhNSk1htG48aNg6urKyIiImpt065dO/B4PHZ5/vy5RB+jR4/Ghg0b2OultfWhp6cHX19fREREYPDgwbXukzLJEyI7bZ15qv1RpZiYGAwdOhSfffaZ1O9TU1NhXCPpwLvXR8eMGYNDhw4hNTUVgwYNqrOPkpISXLp0CbNmzULLli0RFhYmtX14eDjmzp3Lfi4oKKAASggRo/bgOXjwYHh7eyM8PBwhISES3zs4ONRZCG7Lli1YsGABRo4ciR9++EHqjLJmH126dMHFixexcuXKWoMnZZInRHYiqOA5T5p5yiY6Ohqurq5wdnZu8LYMw2Dr1q3Q0dHBqFGj8P3332PIkCF1bsPhcPDmzRt5h0sIqaESDCqVHOyU3Z8qaETw7NatGwIDA/HNN9/ItT3DMIiPjweHw2EDqIeHB/v9kydP8PbtW/a0/bvvvsMHH3ygpNETQrSRRgRPAIiMjMSePXvk3p5hGGzcuBE6Ojrw9fXF8ePH2RtI1TNaLpcLGxsbTJ8+HcuXL1fGsAnRetr6bjtlkpeBNmSSfxclBtE+8maSP3vlL/B4Ss4kX1SIwb0cNfo3pzEzT0JI06StiUEoeBKpaLZGSN0oeBJCFCKC8q9RNoWLRpSSjhBC5EAzTyIV3TAisqJrnoQQIgdtfVSJTtsJIUQOSgueISEhGDt2rMT6dzO+V1RUIC4uDt26dYOBgQHMzc0xcuRInDt3jt1m8+bNMDMzQ3Z2tlhfn3zyCTp27IjXr18DAO7evYtJkyahXbt20NfXh4ODAwICApCeni623ffffw83Nze0aNEC5ubmUsdJCJFP9Wm7shdN16gzT5FIhAkTJiAyMhKzZ8/GzZs3IRQKYWNjAw8PDxw+fBgAMGPGDPTr1w9Tpkxhtz158iQ2b96MpKQkGBoaIj09Hb1790ZWVha2bNmCP//8E4cOHYKLiwvmzZvHbnfgwAFMnDgRkyZNwh9//IFz587ho48+aszDJoQ0Q416zXPv3r3Yv38/jh49itGjR7Prt27diufPn2Pq1KkYPnw4jIyMIBAI0LVrV8THx+Ojjz7C5MmTMXfuXLi7u0MkEiEkJAQdOnRAamoqdHT+9/8Brq6umD17NgCgvLwcs2fPxpo1a8QCcefOnRvvoAlp5kQAKlXQp6Zr1JlncnIyOnbsKBY4q82bNw/Pnz/HL7/8AgCwsbHBunXrMH/+fAQFBYHH4+GLL74AAGRkZODGjRuYN2+eWOCsVp1+7sqVK3j06BF0dHTQs2dPWFlZYeTIkcjMzFTdQRJCtIJSZ57Hjx+XqDFUUVHB/jkrKwudOnWSum31+qysLHbdpEmTsHXrVhw7dgwXL15kc2zeuXMHAODi4lLneP766y8AwPLly/HVV1/B3t4ea9euhYeHB7KystCyZUup25WUlKCkpIT9TGU4CKmdtj6qpNSZp6enJzIyMsSWbdu2ibVpSB6SP/74A1euXIGhoSFSU1Mb3EdlZdXJxOeffw4/Pz/07t0biYmJYBgG+/btq3U7KsNBCKmPUoOnkZERnJycxJa2bduy33fs2BE3b96Uum31+o4dOwIASktL8fHHHyMwMBCbNm3CkiVLcPv2bbE2t27dqnM8VlZWAMSvcerr68PR0REPHjyodbvw8HDk5+ezy7t3/Qkh/6OtNYwa9ZrnhAkTcOfOHRw7dkziu7Vr18LCwgLDhw8HUJXf88WLF4iLi0NwcDCGDx+OSZMmobKyEq6urujcuTPWrl3Lzi5rqn4sqnfv3tDX12eDLgCUlZXh/v37sLOzq3Wc+vr6MDExEVsIIdLRo0qNYMKECRg3bhyCg4MhEAhw//59XLt2DdOnT8fRo0exbds2GBkZ4ffff0dMTAwEAgFMTU0BVNUqun37NuLi4sAwDBITE5GVlYVBgwbhhx9+wF9//YVr165h5cqVGDNmDADAxMQEM2bMQEREBH7++Wfcvn2brVvk7+/fmIdOCGlmGvVRJYZhsHfvXqxbtw5xcXH4z3/+AwMDA/Tv3x9CoRADBgxASUkJgoODMWnSJIwYMYLd1srKCuvXr8eUKVPw3nvvoV+/fkhPT8fKlSsRGhqKZ8+ewcrKCu7u7li3bh273Zo1a8DlcjFx4kS8efMGbm5uOHXqlEQVTkKIfLT19UzKJC8DyiTftFFiENnIm0n+xMUcGPGU+7soLiqAj5u1Rv/mKDEIIUQhlaKqRdl9ajoKnkQqmq0RUjcKnoQQhWjrNU9KSUcIIXKgmSchRCHa+nomBU8iFd1tJ7ISiaoWZfepCvfv38cXX3yBU6dOIS8vD9bW1ggKCsLnn38OPT29BvVFwZMQojVu3bqFyspKbNmyBU5OTsjMzERoaCiKi4sRGxvboL4oeBJCFFIJBpVKvsGj7P6q+fj4wMfHh/3s6OiI27dvY/PmzQ0Ong2+YRQSEgKGYdjFwsICPj4+uHbtGttGJBJh69atcHNzA4/Hg5mZGfr06YN169axJTSWL18OV1fXWvdz8OBBjBgxAhYWFmAYBhkZGRJttm7dCg8PD5iYmIiV+qip5li5XC5sbW0xd+5csZRzhBDNVFBQILao4nebn59fa3rKush1t93Hxwe5ubnIzc3FyZMnweVy8d5777HfT5w4EXPmzMGYMWNw+vRpZGRkYOnSpThy5Ah+/vlnmfZRXFyMgQMHIiYmptY2r1+/ho+PDxYvXlxnX4mJicjNzcXff/+NTZs24bvvvsOXX34p28ESQuqkysQgNjY2Yukho6KilDr2u3fvYv369Zg+fXqDt5XrtF1fXx98Ph8AwOfzsWjRIgwaNAhPnz7F6dOnsWvXLhw+fJhN0AEA9vb2eP/992VOLDxx4kQAVRd4azNnzhwAVUXm6mJmZsaO18bGBmPGjMGVK1dkGgchRH2ys7PFXs+sToj+rkWLFtU50QKq0l7WTKD+6NEj+Pj4wN/fH6GhoQ0em8LXPIuKirBz5044OTnBwsICu3btgrOzs1jgrMYwDJslSV2ysrJw6tQphISE1NqGMskTIjtV3m2XNSXkvHnz6vxNA1XXN6vl5OTA09MT7u7u2Lp1q1xjlCt41iy3UVxcDCsrKxw/fhw6Ojq4c+cOnJ2d5RqMqgQEBIDD4aC8vBwlJSV47733EB4eXmv7qKgorFixohFHSAhRROvWrdG6dWuZ2j569Aienp5sZQlpddBkIddWNcttXLp0Cd7e3hg5ciT++eefBpXZaCxxcXHIyMjAH3/8gePHjyMrK4u9LCANZZInRHZNKZP8o0eP4OHhAVtbW8TGxuLp06fIy8tDXl5eg/uSa+ZZXW6j2rZt22Bqaopvv/0WHTt2rLc8RmPj8/nseJ2dnVFYWIiAgAB8+eWXYsdRTV9fv9ZrK4QQcU0pq9Ivv/yCu3fv4u7du2jXrp3Ydw2d+Cnl3XaGYaCjo4M3b97go48+QlZWFo4cOSLRTiQSIT8/Xxm7VAiHwwEAvHnzRs0jIYQ0ppCQEIhEIqlLQ8k18ywpKWGnuS9fvsSGDRtQVFSE0aNHY8iQITh06BACAgKwZMkSjBgxAq1bt8b169cRFxeHTz75BGPHjgVQFbzefX7T2NgY7du3x4sXL/DgwQPk5OQAAFuHiM/ns3fOq6fbd+/eBQBcv34dxsbGsLW1FXtu69WrV8jLy0NlZSXu3LmDyMhIdOzYsdYyyISQBlBFzaHm+m77iRMn2MqUxsbGcHFxwb59++Dh4QEASE5OxtatW5GQkICVK1eCy+WiQ4cO+Pjjj+Ht7c32k5WVhZ49e4r1PWzYMPz66684evQoJk2axK6fMGECACAiIgLLly8HAMTHx4vd2Bk8eDCAquc6a955q+6HYRjw+XwMHjwYq1atApdLL1gRQuRDZThkQGU4mjZKDCIbectw7DvzDIZKLsPxuqgA/kNaafRvjvJ5EkKIHOi8lUhFszUiq6aUGESZaOZJCCFyoJknIUQhTSkZsjJR8CR1+vpYE/hXXI/ZozX/FLAp09YyHHTaTgghcqCZJyFEIU3p9UxlUmjmWZ1VPjo6Wmz94cOHwTBV026hUCiWzb16WbJkidj3NbPA5+TkoFu3bhg8eDDy8/Ml+mjRogW6dOkikUoqJCSEfXup5vjqynpPCCHyUPi03cDAADExMXj58mWd7W7fvs1mn8/NzcWiRYuktrt37x4GDhwIOzs7/PTTT2L5P6v7+PPPPzF9+nSEhYXh5MmTde63vqz3hBDFVN8wUvai6RQOnl5eXuDz+fWmx7e0tGTfS+fz+Ww+0JquXbuGgQMHon///jh8+DBatGghtQ8HBwd8+umncHBwqDcjfHXWez6fD1dXVyxatAjZ2dl4+vRpww+WEEL+n8LBk8PhYNWqVVi/fj0ePnwodz9paWkYMmQI/Pz8sHPnzjrfOxeJRDhx4gQePHgANzc3mffxbtZ7QojimlI+T2VSyg2jcePGwdXVFRERERAIBFLbvJs7759//hELYOPGjcP48eOxYcOGWvdT3UdJSQkqKysRGRnJJgOpTV1Z72tDZTgIIfVR2t32mJgYDB06FJ999pnU71NTU2FsbMx+Njc3F/t+zJgxOHToEFJTUzFo0KA6+ygpKcGlS5cwa9YstGzZEmFhYbWOy9PTE5s3bwZQlT5v06ZNGDlyJC5dugQ7Ozup21AZDkJkVwkV3G1XbncqobTnPAcPHgxvb+9aawM5ODjAycmJXd6d+W3ZsgUTJkzAyJEjcfbs2Tr76NKlCyZNmoSJEydi5cqVdY6rOuu9k5MT+vbti23btqG4uBjffvttrdtQGQ5CSH2U+pxndHQ0XF1d5SoAxzAMtm7dCh0dHYwaNQrff/89hgwZUuc2HA6nwdnga2a9rw2V4SBEdvR6phJ069YNgYGB+Oabb+TanmEYxMfHg8PhsAG0OsEyADx58gRv375lT9u/++47fPDBB3X2WVfWe0KI4ih4KklkZCT27Nkj9/YMw2Djxo3Q0dGBr68vjh8/zj5wXz2j5XK5sLGxwfTp09ms8rWpL+s9IYTIgzLJy0AbM8lXo8Qg2kPeTPKCn1/B0EjJmeSLCzBlhJlG/+YoMQghhMiBEoOQOtGsjdRHW6950syTEELkQDNPQohCaOZJCCFEZjTzJM3egxn/VvcQFGIbf1DdQ6iTSAXJkJvCzJOCJyFEIVTDiBBCiMzUEjyfPn2KsLAw2NrassmKvb29ce7cObZNWloaRo0aBXNzcxgYGKBbt2746quvUFFRAaCqVIe5ubnEq6AXL16Erq4ufv75ZwC1lwGpfmWTEKIYbc0kr5bTdj8/P5SWlmL79u1wdHTE48ePcfLkSTx//hwAcOjQIXz44YeYNGkSTp8+DTMzM/z6669YsGABzp8/j71798La2hrr16/H9OnTMXLkSHTo0AFv3rxBcHAwpk6dihEjRojt8/bt22JvKlhaWjbqMRNCmpdGD56vXr1CamoqhEIhmzXJzs4O/fr1A1CVsDg0NBTvv/++WIG3qVOnok2bNnj//fexd+9ejB8/HkFBQTh48CBCQkKQmpqK8PBwlJWVYc2aNRL7tbS0hJmZWaMcIyHahKpnNhIejwcej4fDhw+LZWuv9vPPP+P58+dSkyqPHj0aHTt2xO7du9l18fHxuHPnDgIDA7FhwwYkJiZKrY/k6uoKKysrDB8+XOzygDQlJSUoKCgQWwghpKZGD55cLhdJSUnYvn07zMzMMGDAACxevJgtB5yVlQUA6NSpk9TtXVxc2DZA1Yzyiy++QEpKCqZNmyZRlsPKygrx8fE4cOAADhw4ABsbG3h4eNRZOC4qKgqmpqbsYmNjo+hhE9Jsaes1T7XcMPLz80NOTg6OHj0KHx8fCIVC9OrVC0lJSWwbWZM9VVRUICkpCYaGhrhw4QLKy8vFvnd2dsb06dPRu3dvuLu7IyEhAe7u7oiLi6u1T8okTwipj9oeVTIwMMDw4cOxdOlSpKWlISQkBBEREejYsSMA4ObNm1K3u3nzJtsGAGJjY/HXX38hPT0dDx8+xKpVq+rdd79+/XD37t1av9fX14eJiYnYQgiRjmaeata5c2cUFxdjxIgRaNmyJdauXSvR5ujRo7hz5w4CAgIAADdu3EBERAQ2b96MTp06YfPmzfjyyy/ZSwC1ycjIYBMkE0IUU33DSNmLpmv0u+3Pnz+Hv78/Jk+ejO7du8PY2Bjp6elYvXo1xowZAyMjI7YY3LRp0zBr1iyYmJjg5MmTmD9/Pj744AN8+OGHKC8vR3BwMP7973/j3/+uev3Oz88Pfn5+CAkJwaVLl8DlcrFu3To4ODigS5cuePv2LbZt24ZTp06xz4ESQog8Gj148ng8uLm5IS4uDvfu3UNZWRlsbGwQGhqKxYsXAwA++OADnD59GitXrsSgQYPw9u1bdOjQAZ9//jnmzJkDhmGwatUqPHr0SCIIbty4EV26dMGqVauwbNkylJaWYt68eXj06BEMDQ3RvXt3/Prrr/D09GzsQyekWdLWrEpUhkMG2lyGozmgxCCykbcMx9eH89FCyWU43hQXYPZYzf7NUWIQQohCKiurFmX3qekoeJJmT9NTupGmSWPuthNCmqam+qhSSUkJXF1dwTAMMjIyGrw9BU9CiFZasGABrK2t5d6eTttJs0c3jFSrKd5t//HHH/Hzzz/jwIED+PHHH+Xqg4InIUQhlVBBVqX//993k/Lo6+tDX19fob4fP36M0NBQHD58GIaGhnL3Q6fthBCNZWNjI5akJyoqSqH+RCIRQkJCMGPGDPTp00ehvpQSPOvLDG9vbw+GYZCSkiKxbZcuXcAwjFhSkGpRUVHgcDhS83MmJSWxWeE5HA7Mzc3h5uaGyMhI5Ofn1zrW6OhoMAyDOXPmyH28hJD/EYlEKlkAIDs7WyxJT3h4uNQxLFq0SGrFiJrLrVu3sH79ehQWFtbaT0Mo5bS9vszwQNX/gyQmJmLChAnsugsXLiAvLw9GRkZS+01ISMCCBQuQkJCA+fPnS3xvYmKC27dvQyQS4dWrV0hLS0NUVBQSExNx7tw5iYvBv//+O7Zs2YLu3bsr47AJISoma2KeefPmISQkpM42jo6OOHXqFM6fPy9x6t+nTx8EBgZi+/btMo9N4eBZX2b4aoGBgYiLi0N2djabHzMhIQGBgYHYsWOHRL9nzpzBmzdvEBkZiR07diAtLQ3u7u5ibRiGAZ/PB1CVt7NTp04YPXo0unTpggULFmDnzp1s26KiIgQGBuLbb7/Fl19+qehhE0L+nybcMGrdujVat25db7tvvvlG7Pefk5MDb29v7NmzB25ubg3ap8Kn7fVlhq/Wpk0beHt7s5H99evX2LNnDyZPniy1vUAgQEBAAHR1dREQEACBQCDTeCwtLREYGIijR4+yxeIAYObMmfD19YWXl1cDjo4Q0pzY2tqia9eu7FKd3rJ9+/Zo165dg/pSOHjWlxm+psmTJyMpKQkikQj79+9H+/bt4erqKtGuoKAA+/fvR1BQEAAgKCgIe/fuRVFRkUxjcnFxQWFhIXvZICUlBVeuXJH5YjOV4SBEdqLK/72iqaxF1ARez1TKDSNZMsMDgK+vL4qKinD27FkkJCTUOuvcvXs32rdvjx49egCoqj9kZ2eHPXv2yDSe6ovNDMMgOzsbs2fPxq5du2BgYCDT9lSGgxDtYG9vD5FIJHUSVx+lPapUW2b4mrhcLiZOnIiIiAhcvHgRgYGBUvsSCAS4ceMGuFwuu/z5559ISEiQaSw3b96EiYkJLCwscPnyZTx58gS9evVi+zpz5gy++eYbcLlcsVP7alSGgxDZNdXXMxWlsofkO3fujMOHD0usnzx5MmJjYzF+/HiYm5tLfH/9+nWkp6dDKBSiZcuW7PoXL17Aw8MDt27dgouLS637ffLkCZKTkzF27Fjo6Ohg2LBhuH79ulibSZMmwcXFBQsXLgSHw5HoQxkP4hKiLbS19LDCwbO+zPDv6tSpE549e1brk/0CgQD9+vWTqIIJAH379oVAIGCf+xSJRMjLy2MfVTp//jxWrVoFU1NTREdHAwCMjY3RtWtXsX6MjIxgYWEhsZ4QQmSlcPCUJTP8uywsLKSuLy0txc6dO7Fw4UKp3/v5+WHt2rVskbeCggJYWVmBYRiYmJjA2dkZwcHBmD17tsYmUCWkudGER5XUgTLJy4AyyTdtlBhENvJmkv9y1ysYGCr3d/H2dQGWBJpp9G+OEoMQQhQiqhRBpOSLlMruTxUoeJJmT9NTupGmiYInIUQh2nq3nVLSEUKIHGjmSQhRiLbebafgSZq9m37D1T0Epet04Bd1D4FVWSlCpZLPs5XdnyrQaTshhMiBZp6EEIVo62m7Smae9aXDX758OQDg6tWr8Pf3R5s2bWBgYIAOHTogNDQUWVlZAID79+9L3b46Vd0ff/yBgIAA2NjYoEWLFujUqRO+/vprsbHk5ubio48+QseOHaGjo0PlNwghSqGSmWdubi775z179mDZsmW4ffs2u47H4+H48ePw8/ODt7c3du3ahfbt2+PJkyfYt28fli5dKpZ+7tdff0WXLl3Yzy1atAAAXL58GZaWlti5cydsbGyQlpaGadOmgcPhYNasWQCqcnO2bt0aS5YsQVxcnCoOlxCtpq0zT5UEz+rSGABgamoqVi4DqMoiP2nSJIwaNQqHDh1i1zs4OMDNzQ2vXr0S68/CwkJs+2rv5gN1dHTE+fPncfDgQTZ42tvbs7NRWVPaEUJIfdRyzfOnn37Cs2fPsGDBAqnfm5mZyd13fn6+WCo7eZSUlIiVFKFM8oTUrlIkQqWSp4rK7k8V1HK3/c6dOwBQZ17Omtzd3dlaSTweD1evXpXaLi0tDXv27MG0adMUGh9lkieE1EctM8+GJnLas2cPOnXqxH6WFswyMzMxZswYREREYMSIEQqNLzw8HHPnzmU/FxQUUAAlpBYiFdQcago1jNQSPKsr1t26dQv9+/evt72NjQ2cnJxq/f7PP//EsGHDMG3aNCxZskTh8VEmeUJkJ4KowRMiWfrUdGo5bR8xYgRatWqF1atXS/3+3RtGdblx4wY8PT0RHByMlStXKmmEhBBSN7XMPI2MjLBt2zb4+/vj/fffx6effgonJyc8e/YMe/fuxYMHD5CSklJvP5mZmRg6dCi8vb0xd+5c5OXlAQA4HA5at27NtsvIyAAAFBUV4enTp8jIyICenh46d+6skuMjRJtUlx5Wdp+aTm1vGI0ZMwZpaWmIiorCRx99xF5XHDp0KL788kuZ+ti/fz+ePn2KnTt3YufOnex6Ozs73L9/n/3cs2dP9s+XL19GcnKyRBtCCGkIKsMhAyrD0bRRYhDZyFuGY8Hmp9BvodzfRcmbAqwOa63Rvzl6t500e5qUgYg0HxQ8CSEKoUzyhBBCZEYzT0KIQqh6JiHN1I0xQ9U9BJXpcuSUuoegtVmV6LSdEELkQDNPQohCqIaREoSEhIhlfLewsICPjw+uXbsm0Xb69OngcDjYt2+fxHfLly9n++BwOLCxscG0adPw4sULtk1OTg7Mzc3xzTffiG178eJF6Orq4ueffwYAHDx4EMOHD0fr1q1hYmKC/v3746efflLmYRNCtJDST9t9fHyQm5uL3NxcnDx5ElwuF++9955Ym9evXyMlJQULFiyoNUFxly5dkJubiwcPHiAxMREnTpxAWFgY+721tTXWr1+P8PBwNsXdmzdvEBwcjKlTp7KZlc6ePYvhw4fjhx9+wOXLl+Hp6YnRo0fXmtaOENIwIpFIJYumU/ppu76+Ppv1nc/nY9GiRRg0aBCePn3Kvm++b98+dO7cGYsWLYK1tTWys7MlUr5xuVy2n7Zt28Lf3x+JiYlibYKCgnDw4EGEhIQgNTUV4eHhKCsrw5o1a9g269atE9tm1apVOHLkCI4dOyb22iYhhDSESm8YFRUVYefOnXBycoKFhQW7XiAQICgoCKamphg5ciSSkpLq7Of+/fv46aefoKenJ/FdfHw87ty5g8DAQGzYsAGJiYng8Xi19lVZWYnCwkKFs80TQqpU5/NU9qLplD7zPH78OBu8iouLYWVlhePHj0NHpypO37lzBxcuXMDBgwcBVM0e586diyVLloBhGLaf69evg8fjoaKiAm/fvgUAfPXVVxL7s7S0xBdffIEZM2YgLCwMgwcPrnN8sbGxKCoqwocfflhrGyrDQQipj9Jnnp6ensjIyEBGRgYuXboEb29vjBw5Ev/88w+AqiJs3t7eaNWqFQBg1KhRyM/Px6lT4s+rOTs7IyMjA7///jsWLlwIb29vfPLJJxL7q6ioQFJSEgwNDXHhwgWUl5fXOrbk5GSsWLECe/fuhaWlZa3tqAwHIbKrrmGk7EXTKT14GhkZwcnJCU5OTujbty+2bduG4uJifPvtt6ioqMD27dvx/fffg8vlgsvlwtDQEC9evJC4caSnpwcnJyd07doV0dHR4HA4WLFihcT+YmNj8ddffyE9PR0PHz7EqlWrpI4rJSUFU6dOxd69e+Hl5VXnMYSHhyM/P59dsrOz5f8LIYQ0Syp/zpNhGOjo6ODNmzf44YcfUFhYiKtXr4LD4bBtMjMzMWnSJLx69arWyplLlizB0KFDERYWBmtrawBVWeQjIiKQnJyMTp06YfPmzQgICMDYsWPRvXt3dtvdu3dj8uTJSElJga+vb71jpjIchMhOFXfHm8LddqXPPEtKSpCXl4e8vDzcvHkTn3zyCYqKijB69GgIBAL4+vqiR48e6Nq1K7t8+OGHMDMzw65du2rtt3///ujevTs7sywvL0dwcDD+/e9/49///jcAwM/PD35+fggJCWFP35OTk/Hxxx9j7dq1cHNzY8eWn5+v7EMnRCtVPySv7EXTKT14njhxAlZWVrCysoKbmxt+//137Nu3D506dcL3338PPz8/yUHo6GDcuHEQCAR19v3f//4X27ZtQ3Z2NlatWoVHjx5hw4YNYm02btyI3NxcNshu3boV5eXlmDlzJjsuKysrzJ49W3kHTQjROpRJXgaUSb5po8QgspE3k/yMmEcqySQfv7Ctyn5z33//PSIjI3Ht2jUYGBhgyJAhOHz4cIP6oHfbCSFa5cCBAwgNDcWqVaswdOhQlJeXIzMzs8H9UPAkzZ4mpG1rzkQiFeTzVNEJcXl5OWbPno01a9ZgypQp7Hp5KulSSjpCiMYqKCgQW2q+vCKPK1eu4NGjR9DR0UHPnj1hZWWFkSNHyjXzpOBJCFGISAUPyFfPPG1sbMReWImKilJorH/99ReAqsxtS5YswfHjx2Fubg4PDw+xrG2yoOBJCNFY2dnZYi+shIeHS223aNEisXSY0pZbt26hsrLqpfnPP/8cfn5+6N27NxITE8EwjNT0mHWha56k2bvsOUDdQ2gUvU+fU8t+VVnDyMTERKa77fPmzUNISEidbRwdHZGbmwtA/Bqnvr4+HB0d8eDBgwaNkYInIUQhmlAArnXr1mzKy7r07t0b+vr6uH37NgYOHAgAKCsrw/3792FnZ9egfVLwJIRoDRMTE8yYMQMRERGwsbGBnZ0dm//X39+/QX0p5Zrn06dPERYWBltbWzYZsre3N86dqzqNsLe3B8MwSElJkdi2S5cuYBhGak7PqKgocDgcseTG1ZKSksRKdZibm8PNzQ2RkZESr15u3rwZ3bt3Z08B+vfvjx9//FEZh06I1qsUqWZRlTVr1mDChAmYOHEi+vbti3/++QenTp2Cubl5g/pRSvD08/PD1atXsX37dmRlZeHo0aPw8PDA8+fP2TY2NjYSmeAvXLiAvLw8GBkZSe03ISGhzlIdJiYmyM3NxcOHD5GWloZp06Zhx44dcHV1RU5ODtuuXbt2iI6OxuXLl5Geno6hQ4dizJgxuHHjhhKOnhDSlOjq6iI2NhaPHz9GQUEBfvnlF3Tp0qXB/SgcPF+9eoXU1FTExMTA09MTdnZ26NevH8LDw/H++++z7QIDA3HmzBmx9G4JCQkIDAwElyt59eDMmTN48+YNIiMjUVBQgLS0NIk2DMOAz+fDysoKnTp1wpQpU5CWloaioiIsWLCAbTd69GiMGjUKHTp0QMeOHbFy5UrweDxcuHBB0cMnROtVX/NU9qLpFA6ePB4PPB4Phw8frvMB1jZt2sDb2xvbt28HUFUEbs+ePZg8ebLU9gKBAAEBAdDV1UVAQEC9SUOqWVpaIjAwEEePHkVFRYXE9xUVFUhJSUFxcTH69+8vtY+SkhKJh3MJIaQmhYMnl8tFUlIStm/fDjMzMwwYMACLFy+WWm548uTJSEpKgkgkwv79+9G+fXu4urpKtCsoKMD+/fsRFBQEoKpUx969e1FUVCTTmFxcXFBYWCh22aC6rIe+vj5mzJiBQ4cO1fpKFmWSJ0R22lo9U2nXPHNycnD06FH4+PhAKBSiV69eEjeBfH19UVRUhLNnzyIhIaHWWefu3bvRvn179OjRAwDg6uoKOzs77NmzR6bxVP/F16yJVF3W4+LFiwgLC0NwcDD+/PNPqdtTJnlCSH2U9oaRgYEBhg8fjqVLlyItLQ0hISGIiIgQa8PlcjFx4kRERETg4sWLCAwMlNqXQCDAjRs32FIdXC4Xf/75Z603jt518+ZNmJiYiFXsrC7r0bt3b0RFRaFHjx74+uuvpW6vr6/P3pmX9SFdQrRVZaUqEiKr+6jqp7LnPDt37iw1P97kyZMRGxuL8ePHS3004Pr160hPT4dQKBQrD/zixQt4eHjg1q1bcHFxqXW/T548QXJyMsaOHctW7JSmsrJS4SQDhBDtLcOhcPB8/vw5/P39MXnyZHTv3h3GxsZIT0/H6tWrMWbMGIn2nTp1wrNnz2BoaCi1P4FAgH79+kktIdy3b18IBAL2uU+RSIS8vDyIRCK8evUK58+fx6pVq2Bqaoro6Gh2u/DwcIwcORK2trYoLCxEcnIyhEIhfvrpJ0UPnxCipRQOnjweD25uboiLi8O9e/dQVlYGGxsbhIaGYvHixVK3qXk6XVNpaSl27tyJhQsXSv3ez88Pa9euZUtsFBQUwMrKCgzDwMTEBM7OzggODsbs2bPFTrWfPHmCjz/+GLm5uTA1NUX37t3x008/Yfjw4QoePSFEE17PVAcqwyEDKsPRtFFiENnIW4YjaPE96BkYK7Tvd5W+LcTOVe01+jdH77aTZk9d2Ya0hbbOPCmfJyGEyIFmnoQQhVSiKvu7svvUdDTzJIQQOdDMkzR7Zzq5qnsIajHkZkaj7Edbr3lS8CSEKERbH5Kn03ZCCJGD2oNnSEgIxo4dCwDw8PDAnDlzJNokJSXBzMyM/bx8+XIwDIMZM2aItcvIyADDMLh//z4A4P79+2LV86rfb//yyy+bxP+zEdIUiJT+XruW5PNUFwMDAwgEAty5c6fetr/++ityc3Nx584drFixAitXrpQ5yQghhEjTZIOns7MzPD098fnnn9fb1sLCAnw+H3Z2dggMDMSAAQNw5cqVRhglIc0fZZJvgqKjo3HgwAGkp6fLvE16ejouX74MNzc3FY6MENLcNem77b169cKHH36IhQsX4uTJk7W2c3d3h46ODkpLS1FWVoZp06bh448/rrV9SUmJWLo6KsNBSO3obnsT9eWXXyI1NRU///xzrW327NmDjIwM/PHHH9i7dy+OHDmCRYsW1dqeynAQQuqjUcHTxMREouY6UFWh09TUVOo27du3R2hoKBYtWlTr/1vZ2NjAyckJnTp1gr+/P+bMmYO1a9fi7du3UttTGQ5CZCeqrFTJouk06rTd2dlZ6gzyypUr6NixY63bLVu2DO3bt0dKSopM++FwOCgvL0dpaSkMDAwkvtfX14e+vr7sAydEi1U/XqTsPjWdRgXPsLAwbNiwAZ9++immTp0KfX19fP/999i9ezeOHTtW63Zt2rTB3Llz2Qzz73r+/Dny8vJQXl6O69ev4+uvv4anp6fG5gkkhGg+tQfPyspKcLlVw3B0dMTZs2fx+eefw8vLC6WlpXBxccG+ffvg4+NTZz+fffYZNm/eLPVU3MvLC0DVjNPKygqjRo3CypUrlX8whGghbb1hpPbg+eTJEzg5ObGf+/btW+fNH6DqDaPly5eLrTMxMcHTp0/F1tnb2zeJ/wiEkKZHbcHz5cuXOHfuHIRCocRrloSQpoOyKjWyyZMn4/fff8e8efOkVtkkRFkaKzUb0S5qC56HDh1S164JIUqkrTNPjXrOkxBCmgq13zAihDRtlahEpUi5D7VXgh6SJ0TtfjB0UfcQNMKo17dU0q+oUvmn2UqOxSpBp+2EECIHmnkSQhRCN4w01NOnTxEWFgZbW1vo6+uDz+fD29sb586dA1D1IHx1mQ1DQ0N069YN27ZtE+tDKBSKleOoXpYsWaKOQyKENAMaP/P08/NDaWkptm/fDkdHRzx+/BgnT57E8+fP2TaRkZEIDQ3F69evsW/fPoSGhqJt27YYOXKkWF+3b98We5+dx+M12nEQ0lzR65ka6NWrV0hNTYVQKMSQIUMAAHZ2dujXr59YO2NjY/D5fADAwoULsXr1avzyyy8SwdPS0lKskBwhhMhLo4Mnj8cDj8fD4cOH8a9//aveNHGVlZU4dOgQXr58CT09Pbn3S5nkCZFdZWUlKpWcf1PZ/amCRl/z5HK5SEpKwvbt22FmZoYBAwZg8eLFuHbtmli7hQsXgsfjQV9fHx988AHMzc0xdepUif7atWvHBmQejyd26l8TZZInhNRHo4MnUHXNMycnB0ePHoWPjw+EQiF69eqFpKQkts38+fORkZGBU6dOwc3NDXFxcWKZmqqlpqYiIyODXczNzaXukzLJEyI7ba2eqdGn7dUMDAwwfPhwDB8+HEuXLsXUqVMRERGBkJAQAECrVq3g5OQEJycn7Nu3D926dUOfPn3QuXNnsX4cHBxkuuZJmeQJkZ1IVAmRkp9qV3Z/qqDxM09pOnfujOLiYqnf2djYYPz48QgPD2/kURFCmoKsrCyMGTMGrVq1gomJCQYOHIjTp083uB+NDp7Pnz/H0KFDsXPnTly7dg1///039u3bh9WrV9eZxm727Nk4duxYg+q5E0Lk09RO29977z2Ul5fj1KlTuHz5Mnr06IH33nsPeXl5DepHo0/beTweew3z3r17KCsrg42NDUJDQ7F48eJat+vcuTNGjBiBZcuW4YcffmjEERNCNNmzZ89w584dCAQCdO/eHQAQHR2NTZs2ITMzk33kURYaHTz19fURFRWFqKioWtvcv39f6voTJ06wf/bw8GgSD90S0iSpYqb4//29+5igovcjLCws4OzsjB07dqBXr17Q19fHli1bYGlpid69ezeoL40OnoQog6qyCRHVe/cxwYiICIn6ZQ3BMAx+/fVXjB07FsbGxtDR0YGlpSVOnDhR69M3tdHoa56EEM1XKapUyQIA2dnZYo8N1nYjeNGiRVLzV9Rcbt26BZFIhJkzZ8LS0hKpqam4dOkSxo4di9GjRyM3N7dBx82I6Hy2XgUFBTA1NUV+fj7VeifNVkP/nVe3HzohFVw95eaJKC8twqmUQTKP5enTp7W+9FLN0dERqampGDFiBF6+fCnWb4cOHTBlyhQsWrRI5jHSaTshRCGakJKudevWaN26db3tXr9+DQDQ0RE/6dbR0WnwK6EUPEmz972us7qHoDF8y24rvU+RqBIiJb+LrqqH5Pv37w9zc3MEBwdj2bJlaNGiBb799lv8/fff8PX1bVBfdM2TEKI1WrVqhRMnTqCoqAhDhw5Fnz598Ntvv+HIkSPo0aNHg/qimSchRCGacNreEH369MFPP/2kcD8KzTxDQkLAMAxmzJgh8d3MmTPBMAyCg4Ph5eUFb29viTabNm2CmZkZHj58CAA4fvw4hgwZAmNjYxgaGqJv375iCUBqOnDgADw8PGBqagoej4fu3bsjMjISL168AAAkJSWxd9k4HA7Mzc3h5uaGyMhI5OfnK3LYhBCi+Gm7jY0NUlJS8ObNG3bd27dvkZycDFtbWzAMg8TERFy8eBFbtmxh2/z9999YsGAB1q9fj3bt2mH9+vUYM2YMBgwYgIsXL+LatWuYMGECZsyYgc8++0xsn59//jnGjx+Pvn374scff0RmZibWrl2LP/74A9999x3bzsTEBLm5uXj48CHS0tIwbdo07NixA66ursjJyVH00Akh+F9iEGUvmk7h0/ZevXrh3r17OHjwIAIDAwEABw8ehK2tLRwcHABUBdivv/4as2bNwogRI2Bvb48pU6ZgxIgRmDhxIrKzszFv3jzMmTMHq1atYvueN28e9PT08Omnn8Lf3x9ubm64dOkSVq1ahXXr1mH27NlsW3t7ewwfPhyvXr1i1zEMw75uZWVlhU6dOmH06NHo0qULFixYgJ07dyp6+IQQLaWUG0aTJ09GYmIi+zkhIQGTJk0SaxMcHIxhw4Zh8uTJ2LBhAzIzM9mZ6P79+1FWViYxwwSA6dOng8fjYffu3QCAXbt2gcfj4T//+Y/UsdSXcs7S0hKBgYE4evQoKioqpLYpKSlBQUGB2EIIka6yEqisFCl5UfdR1U8pwTMoKAi//fYb/vnnH/zzzz84d+4cgoKCJNpt3boVmZmZmDNnDrZu3co+l5WVlQVTU1NYWVlJbKOnpwdHR0dkZWUBAO7cuQNHR0fo6urKPV4XFxcUFhZSJnlCiNyUcre9devW8PX1RVJSEkQiEXx9fdGqVSuJdpaWlpg+fToOHz6MsWPHyrUvZbwQVd0HwzBSvw8PD8fcuXPZzwUFBRRACamFqFIFz3k2gamn0h5Vmjx5MmbNmgUA2LhxY+075HLB5YrvtmPHjsjPz0dOTg6sra3FvistLcW9e/fg6enJtv3tt99QVlYm9+zz5s2bMDExgYWFhdTvKZM8IaQ+SntI3sfHB6WlpSgrK5P6WFJd/Pz8oKuri7Vr10p8Fx8fj+LiYgQEBAAAPvroIxQVFWHTpk1S+6p5w0iaJ0+eIDk5GWPHjpV4RYsQ0nBNLRmysiht5snhcHDz5k32zw1ha2uL1atXY968eTAwMMDEiROhq6uLI0eOYPHixZg3bx7c3NwAAG5ubliwYAHmzZuHR48eYdy4cbC2tsbdu3cRHx+PgQMHsnfhRSIR8vLyIBKJ8OrVK5w/fx6rVq2CqakpoqOjlXXohGg1ba1hpNQ3jBTJODRnzhw4OjoiNjYWX3/9NSoqKtClSxds3rxZ4s59TEwMevfujY0bNyI+Ph6VlZVo3749PvjgAwQHB7PtCgoKYGVlBYZhYGJiAmdnZwQHB2P27NmUHYkQohBKSScDSknXtFFikP+pKzGIvCnp/jXyR3B1jZQ5TJSXFePCjyM1+jdHF/0IIUQOlBiENHuqSMNG/oceVSK1qr6yQW8akeas+t93Q6/kVZQXK30squhT2Sh4yqCwsBCAZDEqQpqjwsJCmJqa1ttOT08PfD4f6Sc/VMk4+Hw+9PT0VNK3MtANIxlUVlYiJycHxsbGtb6V1NRUvzWVnZ2tsRfklYGOU3YikQiFhYWwtraW+Rnot2/forS0VK791UdPTw8GBgYq6VsZaOYpAx0dHbRr107dw1AJExOTZh1UqtFxykaWGWdNBgYGGh3gVInuthNCiBwoeBJCiBwoeGopfX19RERENPsEKHScRFXohhEhhMiBZp6EECIHCp6EECIHCp6EECIHCp6EECIHCp4E9vb2YBhGbGkOyaI3btwIe3t7GBgYsGWrm5Ply5dL/HdzcXFR97C0Br1hRAAAkZGRCA0NZT8bGxurcTSK27NnD+bOnYv4+Hi4ublh3bp18Pb2xu3bt2Fpaanu4SlNly5d8Ouvv7Kf360PRlSHZp4EQFWw5PP57GJkpNzkto3tq6++QmhoKCZNmoTOnTsjPj4ehoaGSEhIUPfQlIrL5Yr9d5NWtZaoBgVPAgCIjo6GhYUFevbsiTVr1qC8vFzdQ5JbaWkpLl++DC8vL3adjo4OvLy8cP78eTWOTPnu3LkDa2trODo6IjAwEA8ePFD3kLQGzfEJPv30U/Tq1QstW7ZEWloawsPDkZubi6+++krdQ5PLs2fPUFFRgTZt2oitb9OmDW7duqWmUSmfm5sbkpKS4OzsjNzcXKxYsQKDBg1CZmZmk7/s0iSISLO0cOFCEYA6l5s3b0rdViAQiLhcrujt27eNPGrlePTokQiAKC0tTWz9/PnzRf369VPTqFTv5cuXIhMTE9G2bdvUPRStQDPPZmrevHkICQmps42jo6PU9W5ubigvL8f9+/fh7Nz0iqe1atUKHA4Hjx8/Flv/+PFj8Pl8NY1K9czMzNCxY0fcvXtX3UPRChQ8m6nWrVujdevWcm2bkZEBHR2dJntXWk9PD71798bJkycxduxYAFUJrU+ePIlZs2apd3AqVFRUhHv37mHixInqHopWoOCp5c6fP4+LFy/C09MTxsbGOH/+PP773/8iKCgI5ubm6h6e3ObOnYvg4GD06dMH/fr1w7p161BcXIxJkyape2hK89lnn2H06NGws7NDTk4OIiIiwOFwEBAQoO6haQUKnlpOX18fKSkpWL58OUpKSuDg4ID//ve/mDt3rrqHppDx48fj6dOnWLZsGfLy8uDq6ooTJ05I3ERqyh4+fIiAgAA8f/4crVu3xsCBA3HhwgW5zzhIw1BKOkIIkQM950kIIXKg4EkIIXKg4EkIIXKg4EkIIXKg4EkIIXKg4EkIIXKg4EkIIXKg4Ek0RlJSEszMzGRuLxQKwTAMXr16pbIxEVIbCp5EIefPnweHw4Gvr2+DtrO3t8e6devE1o0fPx5ZWVky9+Hu7o7c3FyYmpoCaHjwJUQRFDyJQgQCAT755BOcPXsWOTk5CvXVokWLBiUj0dPTA5/PB8MwCu2XEHlQ8CRyKyoqwp49exAWFgZfX18kJSWJfX/s2DH07dsXBgYGaNWqFcaNGwcA8PDwwD///IP//ve/bOEyQHzmmJWVBYZhJJIXx8XFoX379gDET9uFQiEmTZqE/Px8ts/ly5cjMjISXbt2lRi7q6srli5dquS/EaJNKHgSue3duxcuLi5wdnZGUFAQEhISUJ0q4fvvv8e4ceMwatQoXL16FSdPnkS/fv0AAAcPHkS7du0QGRmJ3Nxc5ObmSvTdsWNH9OnTB7t27RJbv2vXLnz00UcS7d3d3bFu3TqYmJiwfX722WeYPHkybt68id9//51te/XqVVy7dq1ZZVgijY+CJ5GbQCBAUFAQAMDHxwf5+fk4c+YMAGDlypWYMGECVqxYgU6dOqFHjx4IDw8HALRs2RIcDkes6Jw0gYGB2L17N/s5KysLly9fRmBgoERbPT09mJqagmEYtk8ej4d27drB29sbiYmJbNvExEQMGTKk1mTQhMiCgieRy+3bt3Hp0iU2dySXy8X48eMhEAgAVCVUHjZsmEL7mDBhAu7fv48LFy4AqJp19urVq8G1yUNDQ7F79268ffsWpaWlSE5OxuTJkxUaGyGUz5PIRSAQoLy8HNbW1uw6kUgEfX19bNiwAS1atFB4H3w+H0OHDkVycjL+9a9/ITk5GWFhYQ3uZ/To0dDX18ehQ4egp6eHsrIyfPDBBwqPj2g3mnmSBisvL8eOHTuwdu1aZGRksMsff/wBa2tr7N69G927d8fJkydr7UNPTw8VFRX17iswMBB79uzB+fPn8ddff2HChAkN7pPL5SI4OBiJiYlITEzEhAkTlBLciXajmSdpsOPHj+Ply5eYMmUK+4xlNT8/PwgEAqxZswbDhg1D+/btMWHCBJSXl+OHH37AwoULAVQ953n27FlMmDAB+vr6aNWqldR9/fvf/0ZYWBjCwsLg6ekpNtN9l729PYqKinDy5En06NEDhoaGMDQ0BABMnToVnTp1AgCcO3dOGX8NRMvRzJM0mEAggJeXl0TgBKqCZ3p6Olq2bIl9+/bh6NGjcHV1xdChQ3Hp0iW2XWRkJO7fv4/27dvXWTbC2NgYo0ePxh9//CH1RlFN7u7umDFjBsaPH4/WrVtj9erV7HcdOnSAu7s7XFxc4ObmJsdREyKOynAQrSASidChQwf85z//afL1mYhmoNN20uw9ffoUKSkpyMvLo2c7idJQ8CTNnqWlJVq1aoWtW7c26XLKRLNQ8CTNHl2ZIqpAN4wIIUQOFDwJIUQOFDwJIUQOFDwJIUQOFDwJIUQOFDwJIUQOFDwJIUQOFDwJIUQOFDwJIUQO/weIzCdr1x581wAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 300x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dc.plot_barplot(\n",
    "    acts=tf_acts,\n",
    "    contrast='treatment.vs.control',\n",
    "    top=25,\n",
    "    vertical=True,\n",
    "    figsize=(3, 6)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b4cf5b1",
   "metadata": {},
   "source": [
    "MYOCD SRF and JUNB seem to be the most activated in this treatment while IRF1, KLF11 AND ARID1A seem to be inactivated.\n",
    "\n",
    "We can also plot the network of interesting TFs (top and bottom by activity) and color the nodes by activity and target gene expression:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f3256b33-2797-4f3d-8cbe-67f950cedf29",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 750x750 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dc.plot_network(\n",
    "    net=collectri,\n",
    "    obs=mat,\n",
    "    act=tf_acts,\n",
    "    n_sources=['MYOCD', 'SRF', 'IRF1', 'KLF11'],\n",
    "    n_targets=15,\n",
    "    node_size=50,\n",
    "    figsize=(5, 5),\n",
    "    c_pos_w='darkgreen',\n",
    "    c_neg_w='darkred',\n",
    "    vcenter=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da98dd02-84ea-4b29-9231-bbf40378defa",
   "metadata": {},
   "source": [
    "SRF seems to be active in treated cells since their positive targets are up-regulated.\n",
    "\n",
    "If needed, we can also look at a volcano plot of the target genes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "92d55a88",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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tfrAQ+WDmzJlq+fLlVZ1OZ7REC6AGBQVlek9kZKQaFBSkenh4qJaWlqq7u7varl07dfny5Voag8Ggzp49W61UqZJqbW2tNmjQQN26das6cOBAtVKlSkb5HThwQG3YsKFqZWVltCTHwIEDVXt7+wzlt2rVSq1Vq1aG85UqVcqwdMaDBw/UiRMnqlWrVlWtrKzU0qVLq82aNVPnzp2rJiUlqar6v+U1Pvnkkwx58tgSISkpKerIkSNVV1dXVVEUoyVaKlWqlOHZ0vXr108FVH9//wzXdu7cqb788stquXLlVCsrK7VcuXJqnz59MiwnA2S6DMnKlSvVBg0aqNbW1mrJkiXVVq1aqdu3bzdKs3jxYtXb21u1tLRU3dzc1DfffFO9f/++UZqsPtfM/pv9+OOPas2aNVULCwujJVqyykNV0/7dDB48WC1durRqZWWl1qlTJ9OlXR7/zLOS3WVZ9u/frwYFBam1a9dWnZycVEtLS7VixYrqoEGD1MuXLxulfVL99+zZY1S3J/27EUIUP4qq5mFEtxBCiFwZNGgQ4eHhWounEEIUJBnDJ4QQQghRzEnAJ4QQQghRzEnAJ4QQQghRzEnAJ4QQhWD16tUyfk+IXFqyZAmenp7Y2Njg6+vL4cOHs0x75swZunfvjqenJ4qiGO0UlJM8Hz16RFBQEKVKlcLBwYHu3bsTGRmZn49VoCTgE0IIIYTZ2LhxI2PHjmXq1KkcO3aMevXqERAQkGG7yXQJCQlUrlyZDz/8EHd391znOWbMGH7++Wc2bdrE3r17uXnzJt26dSuQZywIMktXCCGEEGbD19eXxo0bs3jxYiBtG0oPDw9GjhzJe++998R7PT09GT16dIb1K5+WZ0xMDK6urqxfv54ePXoAaYvJ+/j4EBoaStOmTfP/QfOZLLxM2n/YmzdvUqJEiQLdKksIIYQoCKqq8uDBA8qVK2e0/V9BefToEUlJSfmSl6qqGX57ra2tsba2zpA2KSmJsLAwJk6cqJ3T6XT4+/tn2Akpu7KTZ1hYGMnJyUbbOXp7e1OxYkUJ+MzJzZs38fDwKOxqCCGEEHly/fp1KlSoUKBlPHr0iHK2DtwnNV/yc3BwMNrBCNL2LZ82bVqGtHfu3CE1NRU3Nzej825ubtre1jmVnTwjIiKwsrLC2dk5Q5qIiIhclWtqEvCBti3S9evXcXR0LOTaCPFkBoOB69evA+Dh4VHgf82bujwhRM7Fxsbi4eFRoNv8pUtKSuI+qayxqYxdHqcCJGBgYNzfGX5/M2vdE3kjAR9oTcmOjo4S8IkiLz4+XttTNS4u7ol7B5tjeUKI3DPlsCQ7dNgp+rxl8t9ZBNn9/S1dujR6vT7D7NjIyMgsJ2TkR57u7u4kJSURHR1t1MqXl3JNTf5UF0KIXIiIiGDkyJFUrlwZa2trPDw8ePHFF9m5cyeAtgSEoijY2tri6enJK6+8wq5du4zyCQ8PR1EUTpw4oZ178OABbdq0oWbNmvzzzz9amjJlyvDgwQOj++vXr691fSUnJ/Puu+9Sp04d7O3tKVeuHAMGDODmzZtG96TXS1EULCwsqFixImPHjiUxMTH/PyhRbCkWCro8HopFzgJUKysrGjZsqP3/DNJ6IXbu3Imfn1+uniM7eTZs2BBLS0ujNBcuXODatWu5LtfUJOATQogcCg8Pp2HDhuzatYtPPvmEU6dOERISQps2bQgKCtLSzZgxg1u3bnHhwgW++uornJ2d8ff3Z9asWVnmHRUVRZs2bYiPj+f33383Go/14MED5s6dm+W9CQkJHDt2jA8++IBjx46xefNmLly4wEsvvZQh7apVq7h16xZXrlzh888/5+uvv+Y///lPLj8R8SxSLHX5cuTU2LFj+fLLL1mzZg3nzp3jzTffJD4+nsGDBwMwYMAAowkYSUlJnDhxghMnTpCUlMSNGzc4ceIEly5dynaeTk5ODB06lLFjx7J7927CwsIYPHgwfn5+ZjFhAwBVqDExMSqgxsTEFHZVhHiquLg4lbSOEDUuLq7YlWcOOnTooJYvXz7Tz+P+/fuqqqpqpUqV1Pnz52e4PmXKFFWn06nnz59XVVVVr1y5ogLq8ePH1WvXrqk1atRQ27Ztqz548EC7Jz3N+PHjVQcHBzUyMlK7Vq9ePXXq1KlZ1vXw4cMqoF69elU7B6g//PCDUbqhQ4eqHTt2zMbTF20HDhxQdTpdps+SmJiofvTRR2rdunVVW1tbtVSpUmqzZs3UlStXqklJSdq/86yO9M/52LFjao8ePdQyZcqo1tbWatWqVdXXXntNvXDhglbWyJEj1eeee061srJS69WrV+DPbcrfsfSyvi9ZQw1xqZmn4/uSNXJV70WLFqkVK1ZUrays1CZNmqgHDx7UrrVq1UodOHCg9j79/z+PH61atcp2nqqqqg8fPlTfeusttWTJkqqdnZ3atWtX9datWzn+/AqLtPAJIUQO3Lt3j5CQEIKCgjIdz/j4LL7Hvf3226iqyo8//mh0/sKFCzRv3pyaNWuybds2HBwcMtzbp08fqlatyowZM7Jd35iYGBRFeWK9/vrrL3bt2oWvr2+28y2qgoODGTlyJPv27TPqyk5KSiIgIIAPP/yQ4cOHc+DAAQ4fPkxQUBCLFi3izJkz3Lp1SzsWLFiAo6Oj0bl33nmHrVu30rRpUxITE1m3bh3nzp1j7dq1ODk58cEHHxjVZciQIfTq1cvUH4HJ6PR579LV6XM35nDEiBFcvXqVxMREDh06ZPRvd8+ePaxevVp77+npiaqqGY7Hd7p5Up4ANjY2LFmyhHv37hEfH8/mzZvNZvweyKQNIYTIkUuXLqGqKt7e3rm638XFhTJlyhAeHm50fsCAATRv3pxNmzah12c+EF5RFD788ENefPFFxowZQ5UqVZ5Y1qNHj3j33Xfp06dPhgHxffr0Qa/Xk5KSQmJiIp07dzbqBjNHcXFxbNy4kaNHjxIREcHq1auZNGkSAAsWLGDfvn0cPXqUBg0aaPdUrlyZnj17kpSUZBTAOzk5oSiK0Q96QkICgwcPpmPHjvzwww/aeS8vL3x9fYmOjtbOLVy4EEjrov/zzz8L6pELlWKpoOjyNklEMcjat6YiLXxCCJEDaj5sTqRmstDsSy+9xO+//87mzZufeG9AQAAtWrTI0Jr0uOTkZF555RVUVWXp0qUZrs+fP58TJ05w8uRJtm7dyl9//cWrr76a84cpQr799lu8vb2pUaMG/fv3Z+XKldp/r3Xr1uHv728U7KWztLTM1uzzX3/9lTt37jBhwoRMrz+tdVeIwiQtfEKYGQsLC9566y3tdXErr6irVq0aiqLkepHXu3fvEhUVhZeXl9H5999/n7p169K3b19UVeWVV17JMo8PP/wQPz8/xo8fn+n19GDv6tWr7Nq1K9PlLtzd3alatSoANWrU4MGDB/Tp04f//Oc/2nlzExwcTP/+/QEIDAwkJiaGvXv30rp1ay5evEjr1q3zlP/FixcBct26W9zoLBR0eWzh00kLn8nIt7cQZsba2polS5YU2/KKOhcXFwICAliyZAmjRo3K0DL0+Dpdj/vss8/Q6XR06dIlw7UPPvgAnU5Hv379UFU1y/FfTZo0oVu3bpnuG5oe7F28eJHdu3dTqlSpbD1Xejfyw4cPs5W+qLlw4QKHDx/WulotLCzo1asXwcHBtG7dOt9aZsX/SJeueZGATwghcmjJkiU0b96cJk2aMGPGDOrWrUtKSgrbt29n6dKlnDt3DkhbRiUiIoLk5GSuXLnC2rVrWbFiBXPmzMmyFe39999Hr9fTr18/DAYDffr0yTTdrFmzqFWrllGra3JyMj169ODYsWNs3bqV1NRUbdsnFxcXrKystLTR0dFERERgMBi4ePEiM2bMoHr16vj4+OTXx2RSwcHBpKSkUK5cOe2cqqpYW1uzePFiqlevnutW2XTVq1cH4Pz582az9poQ6STgE8LMqKrKnTt3gLQV4gt6ZX1Tl2cOKleuzLFjx5g1axbjxo3j1q1buLq60rBhQ6PxclOmTGHKlClYWVnh7u5O06ZN2blzJ23atHli/u+99x46nY5XX30VVVVp1qxZhjTVq1dnyJAhLF++XDt348YNfvrpJyBtQeZ/2717t1GXZvr6YukTE1q2bMns2bPNsts+JSWFr776ik8//ZT27dsbXevSpQvffPMNffv2ZdKkSRw/fjzDOL7k5OQMkzYy0759e0qXLs3HH39sNGkj3dNad4sbnT73s2y1PFLl+8RUFFXaqImNjcXJyYmYmBjZWk0UefHx8dqSHabaWs2U5RUlqqpyP/Q4kT/vBFXF7cV2lGz2nAS9RcyWLVvo1asXt2/fxsnJyejau+++y65du/jjjz944YUXOH36NDNnzqRFixaUKFGCo0eP8tFHHxEcHGwUJK9evZrRo0cbzbwF+PHHH+nZsyeBgYGMGjWKqlWrcufOHb799luuXbvGhg0bgLTZ3HFxcSxbtozdu3ezceNGAGrWrGnU0ppfTPk7ll7WNu862Gcxozy74lNT6Xj+lPz+moD5/SknhBAmoBoM/Dn8ff5ZsxnFIu1H7e9Pg6kwoCt1v5yNopNFDoqK4OBg/P39MwR7AN27d+fjjz/mwoULbN++nfnz5/PFF1/wzjvvYGdnh4+PD6NGjaJ27drZKuvll1/mwIEDzJkzh759+xIbG4uHhwdt27Y12qnktddeY+/evdr79FbFK1euaOvCgWn3vhXPNmnhQ1r4hHmRFj7TuPHNz5wY8I7ROYOqkgo0/mou5ftm3K5MiKeJPXWBCx/MI+rX31EsLCjbI5AaM8diWyFvC/gWRgtfSK26+dLCF3jmT/n9NQFp4RNCiEz88/UPoNOBwcDf6iN+MNznuJqAPXq+W7NZAj6RY3F/XeFAy94YHiaipqaipqRy85ut3N1ziJbHfsKyZMYWyqJM0eXDLF1VWjhNRfokhBAiE8n3YsBgAOCk+pDrahL+iiPv6t1Jvh9TyLUT5ujyJ19ieJTIXynx3FGTAVBTU3l0M5JrKzYWcu1EcScBnxBCZKJUa1+U/3ZXddWVZIFFJQbpXaliYU+p1k0LuXbCHN3dFYohOYVPUm8xOPUKIYbotAsGlbu/Hy3UuuWGotflyyFMQz5pIYTIhNfIgVg4ldCCPgBFr8fC0QGvkQMKsWbCXFk4O6LodCzQV2Sczp3aih2Q9u/K0qlEIdcu59KXZcnrIUxDAj4hzIyFhQUDBw5k4MCBJttazZTlFRU25d1o/sdGyrzYFsVCj2Khp8yLbWn2x0ZsPcoWdvWEGfIY0BUAO0VPa50jFZS05VnU1FTK95MxoaJgySxdZJauEOLJVFUFVZWlWESeGJKTCes5gtu/7EGxsABU1JRUPEcNpObciXlaoqUwZunubNQQe4s8ztJNSaXd0TD5/TWBZ+fPdSGEyCVFUUDWSxN5pLO0pNHmpdzZFUrU/+1FsbSgbLdAnJvULeyq5YqiJ89dssoz3+RkOoX65+qcOXNo3LgxJUqUoEyZMnTp0oULFy4YpWndujWKohgdb7zxhlGaa9eu0alTJ+zs7ChTpgzjx48nJSXFlI8ihMmoqkp8fDzx8fEm2czd1OUJUZwpOh2u/s2p+ekkfD6cYLbBnjA/hdrCt3fvXoKCgmjcuDEpKSlMmjSJ9u3bc/bsWaPFXYcNG8aMGTO093Z2dtrr1NRUOnXqhLu7OwcOHODWrVsMGDAAS0tLZs+ebdLnEcIUEhISTLoQsqnLE0KYB0WvoOS5hU9azk2lUAO+kJAQo/erV6+mTJkyhIWF0bJlS+28nZ0d7u6Zr0L+22+/cfbsWXbs2IGbmxv169dn5syZvPvuu0ybNq1A9iwUQgghnnWKTpfnca0yLtZ0itQnHROTtpipi4uL0fl169ZRunRpateuzcSJE0lISNCuhYaGUqdOHdzc3LRzAQEBxMbGcubMmUzLSUxMJDY21ugQQgghhCiuisykDYPBwOjRo2nevLnRJtZ9+/alUqVKlCtXjj///JN3332XCxcusHnzZgAiIiKMgj1Aex8REZFpWXPmzGH69OkF9CRCCCFE8ZcvW6vl8X6RfUUm4AsKCuL06dP88ccfRueHDx+uva5Tpw5ly5alXbt2XL58mSpVquSqrIkTJzJ27FjtfWxsLB4eHrmruBBCCPEMyo+Fk3Uyhs9kikSX7ogRI9i6dSu7d++mQoUKT0zr6+sLwKVLlwBwd3cnMjLSKE36+6zG/VlbW+Po6Gh0CCGEEEIUV4Ua8KmqyogRI/jhhx/YtWsXXl5eT73nxIkTAJQtm7bSvZ+fH6dOneL27dtamu3bt+Po6EjNmjULpN5CCCHEsy69SzevhzCNQu3SDQoKYv369fz444+UKFFCG3Pn5OSEra0tly9fZv369XTs2JFSpUrx559/MmbMGFq2bEndumlrF7Vv356aNWvy6quv8vHHHxMREcHkyZMJCgrC2tq6MB9PiAKh1+vp0aOH9rq4lSeEMA+Kkg+zdJUi0dH4TCjUrdWy2kZm1apVDBo0iOvXr9O/f39Onz5NfHw8Hh4edO3alcmTJxt1w169epU333yTPXv2YG9vz8CBA/nwww+zve+nbK0mhBDCnBXG1mr7/ZvjYJm3dqO45BSa79gvv78mUOhdupkdgwYNAsDDw4O9e/dy9+5dHj16xMWLF/n4448z/KOoVKkS27ZtIyEhgaioKObOnftMbfIuxLMsIiKCkSNHUrlyZaytrfHw8ODFF19k586dRunmzJmDXq/nk08+yZDH6tWrcXZ2zrKMQYMGaTv9WFpa4ubmxgsvvMDKlSsxGAxGaZcvX07r1q1xdHREURSio6Pz4zGFKHKkS9e8SFuqEMJshYeH07BhQ3bt2sUnn3zCqVOnCAkJoU2bNgQFBRmlXblyJRMmTGDlypW5KiswMJBbt24RHh7O//3f/9GmTRvefvttOnfubLSVY0JCAoGBgUyaNClPzyZEUZc+SzevhzANaQYTwszEx8ebdKszU5eXE2+99RaKonD48GGjetWqVYshQ4Zo7/fu3cvDhw+ZMWMGX331FQcOHKBZs2Y5Ksva2lqb+V++fHmee+45mjZtSrt27Vi9ejWvvfYaAKNHjwZgz549eXs4IYTIR9LCJ4QwS/fu3SMkJISgoKBMg9B/d9EGBwfTp08fLC0t6dOnD8HBwflSh7Zt21KvXj1tIXghniXSpWteJOATQpilS5cuoaoq3t7eT0wXGxvLd999R//+/QHo378/3377LXFxcflSD29vb8LDw/MlLyHMSfpeunk9hGnIJy2EMEvZXWDgm2++oUqVKtSrVw+A+vXrU6lSJTZu3Jhv9chqxQEhhCgqJOATQpilatWqoSgK58+ff2K64OBgzpw5g4WFhXacPXs215M3Hnfu3LlsLRovRHEjXbrmRSZtCCHMkouLCwEBASxZsoRRo0ZlGMcXHR3N9evXOXr0KHv27MHFxUW7du/ePVq3bs358+ef2iX8JLt27eLUqVOMGTMm13kIYa7yI2CTgM90JOATQpitJUuW0Lx5c5o0acKMGTOoW7cuKSkpbN++naVLlxIQEECTJk1o2bJlhnsbN25McHCwti5famqqtnVjOmtra3x8fABITEwkIiKC1NRUIiMjCQkJYc6cOXTu3JkBAwZo90RERBAREaHt933q1ClKlChBxYoVjYJOIYQwJQn4hDAzer2ejh07aq+LW3lZMaSkEHv8LIpOh2N9HxS9nsqVK3Ps2DFmzZrFuHHjuHXrFq6urjRs2JDPPvuMvn378u6772aaX/fu3fn000+ZPXs2kLbkTIMGDYzSVKlSRQvcQkJCKFu2LBYWFpQsWZJ69eqxcOFCBg4ciO5fA8+XLVvG9OnTtffpwWb6DkJCFBfSwmdeCnVrtaJCtlYTomi79cNvnB45jaTIuwDYlHenzrIZlAlsVcg1E6JoKIyt1Y719MfB0jJPecUlJ/Pcph3y+2sCMmlDCFGk3T90kmO93ybp9j3t3KObkRzt+hYPTv9ViDUTQhSWJUuW4OnpiY2NDb6+vhw+fPiJ6Tdt2oS3tzc2NjbUqVOHbdu2GV1P3zrx8ePfWzF6enpmuP7hhx8WyPMVBAn4hBBF2pXPVqd1+6gqj1QDuwyx/Jx6D1C58vnawq6eEM8sRZf3bdVy06W7ceNGxo4dy9SpUzl27Bj16tUjICCA27dvZ5r+wIED9OnTh6FDh3L8+HG6dOlCly5dOH36tJbm1q1bRsfKlStRFIXu3bsb5TVjxgyjdCNHjsxx/QuLBHxCmJn4+Hjs7e2xt7cnPj6+2JX3uAenL6CmpAKw2nCHeYYITqkPMSSn8OCUtPAJUVgKa1mWefPmMWzYMAYPHkzNmjVZtmwZdnZ2WS619NlnnxEYGMj48ePx8fFh5syZPPfccyxevFhL4+7ubnT8+OOPtGnThsqVKxvlVaJECaN0RWmryaeRgE8IM5SQkEBCQkKxLe/f7Cp7wH8ni/TXlWK13otJ+nLoLC2wr+JRKHUSQuSv2NhYoyMxMTHTdElJSYSFheHv76+d0+l0+Pv7Exoamuk9oaGhRukBAgICskwfGRnJL7/8wtChQzNc+/DDDylVqhQNGjTgk08+ISUlJbuPWOgk4BNCFGmeIwZAaloLn4Oip7SSNkhcTTVQ6fW+hVk1IZ5p+bm1moeHB05OTtoxZ86cTMu8c+cOqampuLm5GZ13c3MjIiIi03siIiJylH7NmjWUKFGCbt26GZ0fNWoUGzZsYPfu3bz++uvMnj2bCRMmZOuzKgpkWRYhRJHm6t+cWgs+4Nx7H2F4lASAztaG2gunUNKvwVPuFkIUlPxcluX69etGs3Stra3zlG9erFy5kn79+mFjY2N0fuzYsdrrunXrYmVlxeuvv86cOXMKtb7ZJQGfEKLI8wzqT/l+L3Fn90EUnY7SbZtiUcKhsKslhMgnjo6O2VqWpXTp0uj1eiIjI43OR0ZG4u7unuk97u7u2U7/+++/c+HChWztte3r60tKSgrh4eHUqFHjqekLm3TpCiHMgqWzI2W7tsf9ZX8J9oQoAgpj0oaVlRUNGzZk586d2jmDwcDOnTvx8/PL9B4/Pz+j9ADbt2/PNH1wcDANGzakXr16T63LiRMn0Ol0lClTJkfPUFikhU8IIYQQOfbvMXh5ySOnxo4dy8CBA2nUqBFNmjRhwYIFxMfHM3jwYAAGDBhA+fLltXGAb7/9Nq1ateLTTz+lU6dObNiwgaNHj7J8+XKjfGNjY9m0aROffvpphjJDQ0M5dOgQbdq0oUSJEoSGhjJmzBj69+9PyZIlc/HkpicBnxBmRqfT0apVK+11cStPCCGepFevXkRFRTFlyhQiIiKoX78+ISEh2sSMa9euGX1XNWvWjPXr1zN58mQmTZpEtWrV2LJlC7Vr1zbKd8OGDaiqSp8+fTKUaW1tzYYNG5g2bRqJiYl4eXkxZswYo3F9RZ1srYZsrSaEEMK8FcbWameGvkgJq7xtrfYgKZlawT/L768JSAufEEIIIXKssLp0Re7IJy2EEEIIUcxJwCeEmYmPj8fV1RVXV1eTba1myvKEEGZCUfLnECYhXbpCmKE7d+4U6/KEEEWfouTDwssS8JmMtPAJIYQQQhRz0sInhBBCiByTSRvmRQI+IYQQQuRYfu6lKwqehNZCCCGEEMWctPAJIYQQIsekS9e8SMAnhJnR6XQ0atRIe13cyhNCmAdFl/cuWUW+UkxGAj4hzIytrS1HjhwptuUJIYTIfxLwCSGEECLHZNKGeZGATwghhBA5p9OlHXnNQ5iEfNJCmJmEhAQ8PT3x9PQkISGh2JUnhBAi/0kLnxBmRlVVrl69qr0ubuUJIcyDoih53hpNtlYzHQn4hBBCCJFjsiyLeZFPWgghhBCimJMWPiGEEELkmMzSNS8S8AkhhBAi55R8mKUrKy+bjHzSQgghhBDFnLTwCWFmFEWhZs2a2uviVp4QwkzkQ5cu0qVrMhLwCWFm7OzsOHPmTLEtTwhhHhRFh5LHLtm83i+yTz5pIYQQQohiTlr4hBBCCJFzOiXvXbLSpWsy0sInhJlJSEigVq1a1KpVy2Rbq5myPCGEeUhfeDmvhzANaeETwsyoqsrZs2e118WtPCGEEPlPAj4hhBBC5JgsvGxeJOATQgghRM4pSt4XTpalnkxGOs+FEEIIIYo5aeETQgghRI5Jl655kYBPCCGEEDmny4e9dGWWrslIwCeEmVEUhUqVKmmvi1t5Qggh8p8EfEKYGTs7O8LDw4tteUII86AoSp7/CJQ/Ik1HAj4hhBBC5JySD126speuycgnLYQQQghRzEnAJ4SZefjwIY0bN6Zx48Y8fPiw2JUnhDAP6bN083oI0yjUgG/OnDk0btyYEiVKUKZMGbp06cKFCxeM0jx69IigoCBKlSqFg4MD3bt3JzIy0ijNtWvX6NSpE3Z2dpQpU4bx48eTkpJiykcRwmQMBgNHjx7l6NGjGAyGYleeEMJMKLr8OYRJFOonvXfvXoKCgjh48CDbt28nOTmZ9u3bEx8fr6UZM2YMP//8M5s2bWLv3r3cvHmTbt26addTU1Pp1KkTSUlJHDhwgDVr1rB69WqmTJlSGI8khBBCiAK2ZMkSPD09sbGxwdfXl8OHDz8x/aZNm/D29sbGxoY6deqwbds2o+uDBg3SJqGkH4GBgUZp7t27R79+/XB0dMTZ2ZmhQ4cSFxeX789WUAo14AsJCWHQoEHUqlWLevXqsXr1aq5du0ZYWBgAMTExBAcHM2/ePNq2bUvDhg1ZtWoVBw4c4ODBgwD89ttvnD17lrVr11K/fn06dOjAzJkzWbJkCUlJSYX5eEIIIUTxpVPy58ihjRs3MnbsWKZOncqxY8eoV68eAQEB3L59O9P0Bw4coE+fPgwdOpTjx4/TpUsXunTpwunTp43SBQYGcuvWLe345ptvjK7369ePM2fOsH37drZu3cq+ffsYPnx4jutfWIpUW2pMTAwALi4uAISFhZGcnIy/v7+Wxtvbm4oVKxIaGgpAaGgoderUwc3NTUsTEBBAbGwsZ86cybScxMREYmNjjQ4hhBBCZJ+i6PLlyKl58+YxbNgwBg8eTM2aNVm2bBl2dnasXLky0/SfffYZgYGBjB8/Hh8fH2bOnMlzzz3H4sWLjdJZW1vj7u6uHSVLltSunTt3jpCQEFasWIGvry8tWrRg0aJFbNiwgZs3b+b4GQpDkQn4DAYDo0ePpnnz5tSuXRuAiIgIrKyscHZ2Nkrr5uZGRESElubfwV769fRrmZkzZw5OTk7a4eHhkc9PI4QQQojserwRJjExMdN0SUlJhIWFGTUE6XQ6/P39tYagx4WGhhqlh7SGocfT79mzhzJlylCjRg3efPNN7t69a5SHs7MzjRo10s75+/uj0+k4dOhQjp+3MBSZgC8oKIjTp0+zYcOGAi9r4sSJxMTEaMf169cLvEwhhBCiWMnHLl0PDw+jhpg5c+ZkWuSdO3dITU3NtKEnq0aerBqG/p0+MDCQr776ip07d/LRRx+xd+9eOnToQGpqqpZHmTJljPKwsLDAxcUly3KLmiIR8I0YMYKtW7eye/duKlSooJ13d3cnKSmJ6Ohoo/SRkZG4u7traR6ftZv+Pj3N46ytrXF0dDQ6hDAnpUuXpnTp0sW2PFGw0geov/HGGxmuBQUFoSgKAwcOxN/fn4CAgAxpPv/8c5ydnfnnn3/Ys2cPiqJk+J4G8PT0ZMGCBdr75cuX07p1axwdHbO8Z9asWTRr1gw7O7sMvTuiaFF0unw5AK5fv27UEDNx4kSTPkvv3r156aWXqFOnDl26dGHr1q0cOXKEPXv2mLQeBalQAz5VVRkxYgQ//PADu3btwsvLy+h6w4YNsbS0ZOfOndq5CxcucO3aNfz8/ADw8/Pj1KlTRoM1t2/fjqOjIzVr1jTNgwhhQvb29kRFRREVFYW9vX2xK0+YhoeHBxs2bDBaW/HRo0esX7+eihUroigKq1at4tChQ3zxxRdamitXrjBhwgQWLVpk9Ad6diQkJBAYGMikSZOyTJOUlETPnj158803c/5Qwmw93ghjbW2dabrSpUuj1+szbejJqpEnq4ahrNIDVK5cmdKlS3Pp0iUtj8cnhaSkpHDv3r0n5lOUFGrAFxQUxNq1a1m/fj0lSpQgIiKCiIgI7QvIycmJoUOHMnbsWHbv3k1YWBiDBw/Gz8+Ppk2bAtC+fXtq1qzJq6++ysmTJ/n111+ZPHkyQUFBWf6DEUKIZ91zzz2Hh4cHmzdv1s5t3ryZihUr0qBBAyAtKPzss8945513uHLlCqqqMnToUNq3b8+rr76a4zJHjx7Ne++9p31/Z2b69OmMGTOGOnXq5PyhhGkpSv4cOWBlZUXDhg2NGoIMBgM7d+7UGoIe5+fnZ5Qe0hqGskoP8M8//3D37l3Kli2r5REdHa2tIgKwa9cuDAYDvr6+OXqGwlKoAd/SpUuJiYmhdevWlC1bVjs2btyopZk/fz6dO3eme/futGzZEnd3d6MvKL1ez9atW9Hr9fj5+dG/f38GDBjAjBkzCuORhBDCbAwZMoRVq1Zp71euXMngwYON0gwcOJB27doxZMgQFi9ezOnTp41a/MQzTKek7aWbpyPny7KMHTuWL7/8kjVr1nDu3DnefPNN4uPjtX+7AwYMMOoSfvvttwkJCeHTTz/l/PnzTJs2jaNHjzJixAgA4uLiGD9+PAcPHiQ8PJydO3fy8ssvU7VqVW1Ig4+PD4GBgQwbNozDhw+zf/9+RowYQe/evSlXrlw+fJgFz6IwC1dV9alpbGxsWLJkCUuWLMkyTaVKlTIsoihEcfXw4UM6dOgAwP/93/9ha2tbrMoTptO/f38mTpzI1atXAdi/fz8bNmzIMG5p+fLl1KpVi3379vH999/j6uqaIa/MuncTEhIKpN7i2darVy+ioqKYMmUKERER1K9fn5CQEG1ixrVr19Dp/tee1axZM9avX8/kyZOZNGkS1apVY8uWLdqKIHq9nj///JM1a9YQHR1NuXLlaN++PTNnzjTqKVy3bh0jRoygXbt26HQ6unfvzsKFC0378HlQqAGfECLnDAYDe/fu1V4Xt/KE6bi6utKpUydWr16Nqqp06tQp08k5ZcqU4fXXX2fLli106dIl07x+//13SpQoYXSudevWBVBrUWTkoks20zxyYcSIEVoL3eMym2jRs2dPevbsmWl6W1tbfv3116eW6eLiwvr163NUz6JEAj4hhHiGDRkyRPvhfFJPioWFBRYWWf9keHl5ZZhV+6T0wvz9e5ZtXvIQpiH/bxRCiGdYYGAgSUlJKIqS6RIsQojiQQI+IYR4hun1es6dO6e9LkjpKzGkL3Vx6tQpSpQoQcWKFbUtNa9du8a9e/e4du0aqampnDhxAoCqVavi4OBQoPUTOaTo0o685iFMQgI+IYQoxlRVJfbYGR6cv4ydZwVKNnsuQxpTLT6/bNkypk+frr1v2bIlAKtWrWLQoEEATJkyhTVr1mhp0peI2b17t4wJLGoUJVezbDPkIUxCUbMzVbaYi42NxcnJiZiYGNl1QxR58fHxWktHXFxcgS+GbOryRP5JunOPoz1GcH///9YOK1G7Oo1//ALbiuaxlITIHlP+jqWXFfHlFBztbPKWV8Ij3IfNkN9fE5C2VCHMkJ2dHXZ2dsW2PJE/Tgx+l+iDJ4zOxZ2/zNFub2VrWSwhnkRRdPlyCNOQLl0hzIy9vT3x8fHFtjyRPxLC/yEqZJ/2/qQhgd1qLDUNtrQ/eY6YI6dwblK3EGsohDAlCa2FEKIYevRPxP9eqwamGm5wXn2Iw3+/9hOu/lNYVRPFhU7Jn0OYhLTwCSFEMWRXtVLa1lUGAzaKjm/1VbBEQfnvIPkSNasVcg2F2ZNZumZFPmkhzMyjR4/o1KkTnTp14tGjR8WuPJE/bNxdqfBql7SgD7BSdCiKgqLX49q+BSVqScAnxLNEWviEMDOpqana3tGpqanFrjyRf2ovnoai0/HP1z+gpqSCouDWxZ+6X8wq7KqJ4qAQt1YTOScBnxBCFFN6G2vqLp+F9+xxxF++jm3FstiULVPY1RLFhU6ntSDnKQ9hEhLwCSFEMWdV2gWr0i6FXQ0hRCGSgE8IIYQQOSeTNsyKBHxCCCGEyLn8WFZFlmUxGQmthRBCCCGKOWnhE0IIIUTOKUo+dOlKC5+pSMAnhJmxt7c36T6opi5PCGEmZFkWsyJdukIIIYQQxZy08AkhhBAi52QdPrMin7QQZubRo0f07NmTnj17mmxrNVOWJ4QwE+ldunk9hElIwCeEmUlNTeW7777ju+++M9nWaqYsTwghRP6TLl0hhBBC5JwsvGxWJOATQgghRM4p+TCGTwI+k5FPWgghhBCimJMWPiGEEELknKzDZ1Yk4BNCCCFEzskYPrMin7QQQgghRDEnLXxCmBk7Ozvi4uK018WtPCGEmZAuXbMiLXxCmBlFUbC3t8fe3h7FBF+Wpi7PXISGhqLX6+nUqVOGa0lJSXz88cfUq1cPOzs7SpcuTfPmzVm1ahXJyckoivLEY9q0aVpe3t7eWFtbExERYVRGcnIy7777LnXq1MHe3p5y5coxYMAAbt68WdCPLkSa9J028noIk5BPWgghciE4OJiRI0eyb98+oyArKSmJgIAAPvzwQ4YPH86BAwc4fPgwQUFBLFq0iDNnznDr1i3tWLBgAY6Ojkbn3nnnHQD++OMPHj58SI8ePVizZo1R+QkJCRw7dowPPviAY8eOsXnzZi5cuMBLL71k0s9BCGEepEtXCDOTmJjI66+/DsAXX3yBtbV1sSrPHMTFxbFx40aOHj1KREQEq1evZtKkSQAsWLCAffv2cfToURo0aKDdU7lyZXr27ElSUhL29vbaeScnJxRFwd3dPUM5wcHB9O3bl1atWvH222/z7rvvGt23fft2o/SLFy+mSZMmXLt2jYoVK+b3YwthRFUU1Dy2+uf1fpF90sInhJlJSUlhzZo1rFmzhpSUlGJXnjn49ttv8fb2pkaNGvTv35+VK1eiqioA69atw9/f3yjYS2dpaWkU7D3JgwcP2LRpE/379+eFF14gJiaG33///Yn3xMTEoCgKzs7OOX4mIXJMUf43UzfXhwR8piIBnxBC5FBwcDD9+/cHIDAwkJiYGPbu3QvAxYsX8fb2znMZGzZsoFq1atSqVQu9Xk/v3r0JDg7OMv2jR49499136dOnD46OjnkuXwhRvEjAJ4QQOXDhwgUOHz5Mnz59ALCwsKBXr15aMJbe0pdXK1eu1IJKgP79+7Np0yYePHiQIW1ycjKvvPIKqqqydOnSfClfiKfKc+tePqzjJ7JNxvAJIUQOBAcHk5KSQrly5bRzqqpibW3N4sWLqV69OufPn89TGWfPnuXgwYMcPnzYaNxeamoqGzZsYNiwYdq59GDv6tWr7Nq1S1r3hMnIGD7zIqG1EEJkU0pKCl999RWffvopJ06c0I6TJ09Srlw5vvnmG/r27cuOHTs4fvx4hvuTk5OJj49/ajnBwcG0bNmSkydPGpUzduxYo27d9GDv4sWL7Nixg1KlSuXr8wohig8J+IQQIpu2bt3K/fv3GTp0KLVr1zY6unfvTnBwMKNHj6Z58+a0a9eOJUuWcPLkSf7++2++/fZbmjZtysWLF59YRnJyMl9//TV9+vTJUMZrr73GoUOHOHPmDMnJyfTo0YOjR4+ybt06UlNTiYiIICIigqSkJBN9IuKZVohdukuWLMHT0xMbGxt8fX05fPjwE9Nv2rQJb29vbGxsqFOnDtu2bdOuZXdNS09PzwxrZn744Ye5qn9hkIBPCCGyKTg4GH9/f5ycnDJc6969O0ePHuXChQts376dCRMm8MUXX9C0aVMaN27MwoULGTVqFLVr135iGT/99BN3796la9euGa75+Pjg4+NDcHAwN27c4KeffuKff/6hfv36lC1bVjsOHDiQb88sRJbSd9rI65FDGzduZOzYsUydOpVjx45Rr149AgICuH37dqbpDxw4QJ8+fRg6dCjHjx+nS5cudOnShdOnTwM5W9NyxowZRmtmjhw5Msf1LyyKml8jjM1YbGwsTk5OxMTEyPgXUeSpqsqdO3cAKF26dIHvfmHq8ooSQ0oKN9b9xM0NP5Oa8AjXgOep9EZfrFycC7tqQhgx5e9Yelm3/m81jvZ5224xNj6Bsh0G5ajevr6+NG7cmMWLFwNgMBjw8PBg5MiRvPfeexnS9+rVi/j4eLZu3aqda9q0KfXr12fZsmWZlnHkyBGaNGnC1atXtTUtPT09GT16NKNHj87hUxYN0sInhJlRFAVXV1dcXV1NtrWaKcsrKtTUVI69Moo/X5vInV2h3D9wjL+mL+KPJl1JjLxT2NUTovDl49ZqsbGxRkdiYmKmRSYlJREWFoa/v/+/qqHD39+f0NDQTO8JDQ01Sg8QEBCQZXrIek3LDz/8kFKlStGgQQM++eQTs1qbVAI+IYTIROTPu4j8eWfaG4OKqqqkpqby6J9ILs3JvFVAiGdJ+izdvB4AHh4eODk5acecOXMyLfPOnTukpqbi5uZmdN7NzS3DftPpIiIicpQ+qzUtR40axYYNG9i9ezevv/46s2fPZsKECdn+vAqbLMsihJlJTExk7NixAMybN88kW6uZsryiIuLHHSh6PWpqKmfUh3yWGkEqKivw4tb3IdRaMLmwqyhEsXH9+nWj4KqwvmeetKZl+vcgQN26dbGysuL1119nzpw5ZvG9KAGfEGYmJSWFzz//HICPP/64wL9oTF1ekaGqpA9wVlGpp9jRTueIoiioBkOhVk2IIiE/Fk7+7/2Ojo7ZGsNXunRp9Ho9kZGRRucjIyMz3Y8awN3dPVvpc7qmpa+vLykpKYSHh1OjRo2n1r2wSZeuEEJkwq1zG0hNBaC2YkeQ3g1vxRZFr8e9a/tCrp0QhU9VdPly5ISVlRUNGzZk586d2jmDwcDOnTvx8/PL9B4/Pz+j9ADbt283Sp+bNS1PnDiBTqejTJkyOXqGwiItfEIIkQm3Li9Q2r85d3buBxRQVdDrsHIrRbWJbxZ29YR4Zo0dO5aBAwfSqFEjmjRpwoIFC4iPj2fw4MEADBgwgPLly2vjAN9++21atWrFp59+SqdOndiwYQNHjx5l+fLlANqalseOHWPr1q3ampYALi4uWFlZERoayqFDh2jTpg0lSpQgNDSUMWPG0L9/f0qWLFk4H0QOScAnhBCZ0FlY0PjHZVwL3sSNb37GkPAQ18BWeI0cgLVb6cKunhCFL5fr6GXII4d69epFVFQUU6ZMISIigvr16xMSEqJNzLh27Ro63f9aDps1a8b69euZPHkykyZNolq1amzZskVbEzN9TUuA+vXrG5W1e/duWrdujbW1NRs2bGDatGkkJibi5eXFmDFjjMb1FXW5XocvOTmZiIgIEhIScHV1xcXFJb/rZjKyDp8wJ/Hx8Tg4OAAQFxeHvb19sSpPCJFzhbEO3z87v8XRIY/r8MUlUKHdK/L7awI56jx/8OABS5cupVWrVjg6OuLp6YmPjw+urq5UqlSJYcOGceTIkYKqqxBCCCGEyIVsB3zz5s3D09OTVatW4e/vz5YtWzhx4gR//fUXoaGhTJ06lZSUFNq3b09gYOBT94sUQgghhBkrpK3VRO5kewzfkSNH2LdvH7Vq1cr0epMmTRgyZAjLli1j1apV/P7771SrVi3fKiqESGNra8uVK1e018WtPCGEmVCUfFiWRQI+U8l2wPfNN99kK521tTVvvPFGriskhHgynU6Hp6dnsS1PCCFE/suXdfhiY2PZsmUL586dy4/shBBCCFHE5efWaqLg5Srge+WVV1i8eDEADx8+pFGjRrzyyivUrVuX77//Pl8rKIQwlpSUxPjx4xk/fjxJSUnFrjwhhJlI32kjr4cwiVx90vv27eP5558H4IcffkBVVaKjo1m4cCH/+c9/8rWCQghjycnJzJ07l7lz55KcnFzsyhNCCJH/chXwxcTEaOvuhYSE0L17d+zs7OjUqZPMzhVCCCGeASpKvhzCNHIV8Hl4eBAaGkp8fDwhISG0b5+2r+T9+/exsbHJdj779u3jxRdfpFy5ciiKwpYtW4yuDxo0CEVRjI7AwECjNPfu3aNfv344Ojri7OzM0KFDiYuLy81jCSGEECKbCmMvXZF7ufqkR48eTb9+/ahQoQLlypWjdevWQFoAV6dOnWznEx8fT7169ViyZEmWaQIDA7l165Z2PD5buF+/fpw5c4bt27ezdetW9u3bx/Dhw3PzWEIIIYQQxVKu9tJ96623aNKkCdevX+eFF17Q9qyrXLlyjsbwdejQgQ4dOjwxjbW1Ne7u7pleO3fuHCEhIRw5coRGjRoBsGjRIjp27MjcuXMpV65ctusihBBCiBzIj0kX0sJnMrn+pBs1akTXrl21PTYBOnXqRPPmzfOlYun27NlDmTJlqFGjBm+++SZ3797VroWGhuLs7KwFewD+/v7odDoOHTqUZZ6JiYnExsYaHUII85I+5COzdT+DgoJQFIVBgwblOO2/0yuKgpWVFVWrVmXGjBmkpKQAad9LL7/8MmXLlsXe3p769euzbt26AnlOIYoqWZbFvGS7hW/s2LHZznTevHm5qszjAgMD6datG15eXly+fJlJkybRoUMHQkND0ev1REREUKZMGaN7LCwscHFxISIiIst858yZw/Tp0/OljkKIwuPh4cGGDRuYP3++tgvIo0ePWL9+PRUrVsx1Wkj7/lm1ahWJiYls27aNoKAgLC0tmThxIgcOHKBu3bq8++67uLm5sXXrVgYMGICTkxOdO3cu+AcXQogcynbAd/z48WylU/IxWu/du7f2uk6dOtStW5cqVaqwZ88e2rVrl+t8J06caBTAxsbG4uHhkae6CmEqtra2nD59Wntd3MrLieeee47Lly+zefNm+vXrB8DmzZupWLEiXl5euU4LxsNJ3nzzTX744Qd++uknJk6cyKRJk4zSvv322/z2229s3rxZAj7xzMiPSRcyacN0sh3w7d69uyDrkS2VK1emdOnSXLp0iXbt2uHu7s7t27eN0qSkpHDv3r0sx/1B2he5tbV1QVdXiAKh0+my3NO6OJSXU0OGDGHVqlVaELdy5UoGDx7Mnj178pT2cba2tkZDSh4XExODj49Prp5BCLOkKHnfC1e6dE3GrELrf/75h7t371K2bFkA/Pz8iI6OJiwsTEuza9cuDAYDvr6+hVVNIYQJ9e/fnz/++IOrV69y9epV9u/fT//+/fOcNp2qquzYsYNff/2Vtm3bZprm22+/5ciRIwwePDjPzyOEEAUhV7N0AY4ePcq3337LtWvXMmy3tHnz5mzlERcXx6VLl7T3V65c4cSJE7i4uODi4sL06dPp3r077u7uXL58mQkTJlC1alUCAgIA8PHxITAwkGHDhrFs2TKSk5MZMWIEvXv3lhm6othKSkpi9uzZAEyaNAkrK6tiVV5Oubq60qlTJ1avXo2qqnTq1InSpUvnOe3WrVtxcHAgOTkZg8FA3759mTZtWoZ0u3fvZvDgwXz55ZdFuiVUiHyXH+voSZeuyeQq4NuwYQMDBgwgICCA3377jfbt2/PXX38RGRlJ165ds53P0aNHadOmjfY+fVzdwIEDWbp0KX/++Sdr1qwhOjqacuXK0b59e2bOnGnUHbtu3TpGjBhBu3bt0Ol0dO/enYULF+bmsYQwC8nJydqko/Hjxxd4AGbq8nJjyJAhjBgxAuCJ63rmJG2bNm1YunQpVlZWlCtXDguLjF+Xe/fu5cUXX2T+/PkMGDAgD08ghPnJj50yZKcN08lVwDd79mzmz59PUFAQJUqU4LPPPsPLy4vXX39d627NjtatW6OqapbXf/3116fm4eLiwvr167NdphCi+AkMDCQpKQlFUbQegLymtbe3p2rVqlle37NnD507d+ajjz6Sxd6FEEVergK+y5cv06lTJwCsrKyIj49HURTGjBlD27ZtZckTIYRJ6fV6zp07p73Or7RZ2b17N507d+btt9+me/fu2jJQVlZW2j7jQhR3MkvXvOTqky5ZsiQPHjwAoHz58tqSDdHR0SQkJORf7YQQAlBTU4nctoe/568iYst2DMnJGdI4Ojri6OiYrfxykjYza9asISEhgTlz5lC2bFnt6NatW67zFMLsKPxvpm6uj8J+iKJpxowZmcZTDx8+ZMaMGbnKU1Gf1Keahb59+9KoUSPGjh3LzJkzWbRoES+//DLbt2/nueeey/akjaIiNjYWJycnYmJi8vQjIIQpxMfHazvcxMXFYW9vX6zKe9zDazc5FDiY+IvhoNOBwYBNBXd8/28lDt5VTFoXIYoqU/6OpZd1+dBOSvxrt63ceBAXRxXfdvL7+xi9Xs+tW7cybC5x9+5dypQpQ2pqao7zzFWX7uLFi3n06BEA77//PpaWlhw4cIDu3bszefLk3GQphBCZOtZvLAl/X097YzAAkHgriqPd3qLVmZB8XexdCJF9KjrUPK7ultf7iytVVTP9bjt58mSuh43kKuD7d2E6nY733nsvV4ULIcSTxF34m+iD/9vlZ7chltPqQ95SyxB/MZz7B47h0rxhIdZQiGdXfuyFK3vpGitZsqS2j3f16tWNgr7U1FTi4uIy3RM8O3IV8Pn7+9O/f3+6desmTbBCmJiNjQ2HDx/WXhe38v4tMfKO9vqRauBLQxS1FVsMgP6x60IIYe4WLFiAqqoMGTKE6dOn4+TkpF2zsrLC09MTPz+/XOWdq4CvVq1aTJw4kbfeeotOnTrRv39/OnbsiKWlZa4qIYTIPr1eT+PGjYttef9WomZVFAsL1JQUbBQd6y2Mx+w51a9ZKPUSQsgs3YIwcOBAALy8vGjWrFm+xlW5+qQ/++wzbty4wZYtW7C3t2fAgAG4ubkxfPhw9u7dm2+VE0I826xKu1Dp9T4Z99vU6SjbqxN2lT0Kp2JCCG3h5bweIqNWrVqh1+v566+/+OOPP9i3b5/RkRu53lpNp9PRvn172rdvz7Jly/j555+ZNWsWwcHBuZo9IoTInqSkJD777DMA3n77bZNsrWbK8h7nM/c99A52hC/5mtS4BHQ2VlQc2gvvD8ebtB5CCGEqBw8epG/fvly9ejXDBhWKouQqzsrVsiz/FhERwYYNG1i7di3Hjh2jSZMmHDx4MC9ZmpwsyyLMybO2LEu61EeJJEZEYV2mFHo720KpgxBFVWEsy3L+6P58WZbFu1Fz+f19TP369alevTrTp0+nbNmyGWbs/ntsX3blqoUvNjaW77//nvXr17Nnzx4qV65Mv3792LhxI1WqyLpYQoj8p7exxs6zQmFXQwjxXzJLt+BcvHiR77777onbO+ZUrsbwubm58f7771O7dm1CQ0O5cOECU6ZMkWBPCFEoBg0apC1l8O8jMDAQAE9PT+2cra0tnp6evPLKK+zatcson/DwcBRFoUyZMtpuQunq16/PtGnTtPebN2+mffv2lCpVCkVROHHiREE/phDiGeHr68ulS5fyNc9ctfD99NNPtGvXDp1OZtcIIYqGwMBAVq1aZXTO2tpaez1jxgyGDRtGUlIS4eHhrF27Fn9/f2bOnMn7779vdN+DBw+YO3fuE/cFj4+Pp0WLFrzyyisMGzYsfx9GCDOQH5MuZNLG//z555/a65EjRzJu3DgiIiKoU6dOhtm6devWzXH+uQr4XnjhBQBu377NhQsXAKhRo0aGLUCEEMJUrK2tcXd3z/J6iRIltOsVK1akZcuWlC1blilTptCjRw9q1KihpR05ciTz5s0jKCgoy++1V199FUhrFRTiWSTLsuSv+vXroyiK0SSNIUOGaK/Tr+V20kauPukHDx7w6quvUr58eVq1akWrVq0oX748/fv3JyYmJjdZCiGEyb399tuoqsqPP/5odL5Pnz5UrVo115uUCyFETl25coW///6bK1euZHqkX/v7779zlX+uAr7XXnuNQ4cOsXXrVqKjo4mOjmbr1q0cPXqU119/PVcVEUKIvNi6dSsODg5Gx+zZs594j4uLC2XKlMnQSqcoCh9++CHLly/n8uXLBVhrIcyXrMOXvypVqpTtIzdy1aW7detWfv31V1q0aKGdCwgI4Msvv9QGSQshCoaNjQ27d+/WXhe38nKrTZs2LF261OhcdjYZz2qT8oCAAFq0aMEHH3zA+vXr862eQhQXKvnQpZu7dqdi76effsr0vKIo2NjYULVqVby8vHKUZ64CvlKlSmW6BoyTkxMlS5bMTZZCiGzS6/W0bt262JaXW/b29jlewuDu3btERUVl+cX54Ycf4ufnx/jxssizEMJ0unTpkmE8HxiP42vRogVbtmzJdtyVq9B68uTJjB07loiICO1cREQE48eP54MPPshNlkIIYXKfffYZOp2OLl26ZHq9SZMmdOvWjffee8+0FRPCDBRml+6SJUvw9PTExsYGX19fDh8+/MT0mzZtwtvbGxsbG+rUqcO2bduMn0VVmTJlCmXLlsXW1hZ/f38uXrxolObevXv069cPR0dHnJ2dGTp0KHFxcbmq/9Ns376dxo0bs337dmJiYoiJiWH79u34+vqydetW9u3bx927d3nnnXeynWeuWviWLl3KpUuXqFixIhUrVgTg2rVrWFtbExUVxRdffKGlPXbsWG6KEEJkITk5meXLlwMwfPjwfN1cuyiUl1uJiYlGf4QCWFhYULp0aSBtsllERATJyclcuXKFtWvXsmLFCubMmfPElsFZs2ZRq1YtLCyMvy7v3bvHtWvXuHnzJoC2YoG7u/sTZwsLUVykLbyc11m6OQ/4Nm7cyNixY1m2bBm+vr4sWLCAgIAALly4kOms+gMHDtCnTx/mzJlD586dWb9+PV26dOHYsWPUrl0bgI8//piFCxeyZs0avLy8+OCDDwgICODs2bPaUJZ+/fpx69Yttm/fTnJyMoMHD2b48OEFMuTj7bffZvny5TRr1kw7165dO2xsbBg+fDhnzpxhwYIFRrN4nyZXW6s9aW2qx02dOjWn2ZucbK0mzMmzurXakwwaNIg1a9ZkOF+jRg3Onz+Pp6cnV69eBcDKygp3d3eaNm3KG2+8QZs2bbT04eHheHl5cfz4cerXr6+df/3111m+fDlTp07VFl9evXo1gwcPzlDmv9MIYSqFsbXayePHKFGiRJ7yevDgAfUaPJejevv6+tK4cWMWL14MgMFgwMPDg5EjR2baGt+rVy/i4+PZunWrdq5p06bUr1+fZcuWoaoq5cqVY9y4cVqLWUxMDG5ubqxevZrevXtz7tw5atasyZEjR2jUqBEAISEhdOzYkX/++Ydy5crl6XN4nK2tLUeOHNEC0nSnTp2iSZMmPHz4kKtXr+Lj40NCQkK28sxVC585BHFCiOIp7q8rXJr9ObdD9qG3saZ835f48rNFrF69Ost7srtWnqenZ4YxMwBffPGFUc8FpAWZgwYNykHNhShe8nPh5djYWKPz1tbWRgunp0tKSiIsLIyJEydq53Q6Hf7+/oSGhmZaRmhoKGPHjjU6FxAQwJYtW4C05VAiIiLw9/fXrjs5OeHr60toaCi9e/cmNDQUZ2dnLdgD8Pf3R6fTcejQIbp27ZqzB3+Khg0bMn78eL766itcXV0BiIqKYsKECTRu3BhI237Nw8Mj23lmuy02Fw2BQgiRr+L+usJ+vx7c3PgLyXejeXQjksvzgglt15/UR4mFXT0hninpe+nm9QDw8PDAyclJO+bMmZNpmXfu3CE1NRU3Nzej825ubhmGdKSLiIh4Yvr0/31amse7iy0sLHBxccmy3LwIDg7mypUrVKhQgapVq1K1alUqVKhAeHg4K1asANJ6XCZPnpztPLPdwlerVi2mTJlCt27dsLKyyjLdxYsXmTdvHpUqVZKBzkKIfHVpzlJSEx6ipqStMp+oGrBOhQcnz3Pzm5/xGNyjkGsohMiN69evG3XpZta69yypUaMGZ8+e5bfffuOvv/7Szr3wwgvatrZZTTbLSrYDvkWLFvHuu+/y1ltv8cILL9CoUSPKlSuHjY0N9+/f5+zZs/zxxx+cOXOGESNG8Oabb+aoIkII8TRRv/6uBXurUqP4Xr3PYn0lPPW23NkVKgGfECakqgqqmscu3f/e7+jomK0xfKVLl0av1xMZGWl0PjIyMsvJUu7u7k9Mn/6/kZGRlC1b1ihN+lhed3d3bt++bZRHSkoK9+7dK7BJWjqdjsDAwHxb3zjbAV+7du04evQof/zxBxs3bmTdunVcvXqVhw8fUrp0aRo0aMCAAQPo16+frMUnhCgQOtv/LfxcW7HFS7GmElYoOgWdzbPdIiCE6enyYeHknN1vZWVFw4YN2blzp9bCZTAY2LlzJyNGjMj0Hj8/P3bu3Mno0aO1c9u3b8fPzw8ALy8v3N3d2blzpxbgxcbGcujQIa3xys/Pj+joaMLCwmjYsCEAu3btwmAw4Ovrm6NnyMrChQsZPnw4NjY2LFy48IlpR40aleP8czxpo0WLFkY7bAghhKmU7/sSlz9ZDqkGGusctPNqSirlenUqxJoJIUxl7NixDBw4kEaNGtGkSRMWLFhAfHy8Nmt+wIABlC9fXhsH+Pbbb9OqVSs+/fRTOnXqxIYNGzh69Ki23JSiKIwePZr//Oc/VKtWTVuWpVy5clpQ6ePjQ2BgIMOGDWPZsmUkJyczYsQIevfunW8zdOfPn0+/fv2wsbFh/vz5WaZTFMU0AZ8QonBZW1trywuYYpyLqct7kqoThhH12+/EHjsDej2KkhbsVRzWi9Ltmj09AyFEvsnPWbo50atXL6KiopgyZQoRERHUr1+fkJAQbdLFtWvXtHFuAM2aNWP9+vVMnjyZSZMmUa1aNbZs2WK05MmECROIj49n+PDhREdH06JFC0JCQoy2k1y3bh0jRoygXbt26HQ6unfv/tSWuJy4cuVKpq/zS47X4btz5w4rV64kNDRUm5ni7u6On58fgwcP1qYPmxNZh08I85GamMStjb8QtWM/elsbyr3SkVJt/TLdD1eIZ0VhrMN39PgZHPK4Dl/cgwc0alBLfn+zkJSUxJUrV6hSpUqGxd9zKked50eOHKF69eosXLgQJycnWrZsScuWLXFycmLRokV4e3tz9OjRPFVICCGeRG9tRYUBXWnw1VzqfvEfSrdrJsGeEKJYSUhIYOjQodjZ2VGrVi2uXbsGwMiRI/nwww9zlWeOwsWRI0fSs2dPli1bluELVlVV3njjDUaOHJnl4odCiLxLTk5m3bp1QNpWP6bYWs2U5QkhzENhdek+CyZOnMjJkyfZs2eP0Sxdf39/pk2blqtl73LUpWtra8vx48fx9vbO9Pr58+dp0KABDx8+zHFFCpN06QpzIlurCSEeVxhduoePn8uXLt0mDXzk9/cxlSpVYuPGjTRt2pQSJUpw8uRJKleuzKVLl3juuecy7EySHTnq0nV3d+fw4cNZXj98+HCGlaqFEEIIIUT2RUVFZdjZA9L+AM/tEJYcdem+8847DB8+nLCwMNq1a6cFd5GRkezcuZMvv/ySuXPn5qoiQgghhDAf+bnwsjDWqFEjfvnlF0aOHAmgBXkrVqzQ1g/MqRwFfEFBQZQuXZr58+fz+eefk5qatuK9Xq+nYcOGrF69mldeeSVXFRFCCCGE+ZAxfAVn9uzZdOjQgbNnz5KSksJnn33G2bNnOXDgAHv37s1VnjleIrtXr14cPHiQhIQEbty4wY0bN0hISODgwYMS7AkhhBBC5FGLFi04efIkKSkp1KlTh99++40yZcoQGhqq7fSRU7le1MXS0tJozzkhhBBCPDukha/gDBgwgDZt2vDee+9RpUqVfMkzr5vgGbl8+TJt27bNzyyFEEIIUQSlB3x5PURGVlZWzJkzh+rVq+Ph4UH//v1ZsWIFFy9ezHWe+bq1WlxcXK77loUQ2WNtbc23336rvS5u5QkhxLNuxYoVANy4cYN9+/axd+9ePv30U15//XXKli3LP//8k+M8cxTwPW3PuBs3buS4AkKInLGwsKBnz57FtjwhhHlQyYdZutLC90QlS5akVKlSlCxZEmdnZywsLHK9hW2OAr7Ro0dTtmxZrKysMr2elJSUq0oIIYQQwrwYUDDkMWDL6/3F1aRJk9izZw/Hjx/Hx8eHVq1a8d5779GyZUtKliyZqzxzFPBVqlSJjz76KMvZuCdOnMj17BEhRPakpKTwww8/ANC1a9c8b6hd1MoTQohn3YcffoirqytTp06lW7duVK9ePc955uibu2HDhoSFhWUZ8CmKQg52ahNC5EJiYqL2/8G4uLgCD8BMXZ4QwjzILN2Cc/z4cfbu3cuePXv49NNPsbKyolWrVrRu3ZrWrVvnKgDM0SzdGTNmPHEsT82aNbly5UqOKyGEELkVERHByJEjqVy5MtbW1nh4ePDiiy+yc+dOAE6ePMlLL71EmTJlsLGxwdPTk169enH79m0AwsPDURRFO1xcXGjVqhW///67UTnTpk3T0lhYWODp6cmYMWOIi4vTyunTpw8eHh7Y2tri4+PDZ599ZtoPQwgTSt9pI6+HyKhevXqMGjWKzZs3ExUVxbZt27CysiIoKAgfH59c5ZmjP9Vr1qz5xOuWlpZUqlQpVxURQoicCg8Pp3nz5jg7O/PJJ59Qp04dkpOT+fXXXwkKCuL333+nXbt2dO7cmV9//RVnZ2fCw8P56aefiI+PN8prx44d1KpVizt37jBr1iw6d+7MX3/9ZbQ/eK1atdixYwcpKSns37+fIUOGkJCQwBdffEFYWBhlypRh7dq1eHh4cODAAYYPH45er2fEiBGm/miEEGZMVVWOHz/Onj172LNnD3/88QexsbHUrVuXVq1a5SpP6ZsRQpitt956C0VROHz4MPb29tr5WrVqMWTIEPbs2UNMTAwrVqzQuqK9vLxo06ZNhrxKlSqFu7s77u7uTJo0iQ0bNnDo0CFeeuklLY2FhQXu7u5A2q5DO3fu5KeffuKLL75gyJAhRvlVrlyZ0NBQNm/eLAGfKJZU8t4lK4PAMufi4kJcXBz16tWjVatWDBs2jOeffx5nZ+dc55mrgK9BgwbaRr7/pigKNjY2VK1alUGDBmX6pSqEEPnh3r17hISEMGvWLKNgL52zszPu7u7apJMePXpk+r31uIcPH/LVV18BZLkiQTpbW9snrk4QExODi4vLU8sUwhzlR5esdOlmbu3atTz//PM4OjrmW5652mkjMDCQv//+G3t7e9q0aUObNm1wcHDg8uXLNG7cmFu3buHv78+PP/6YbxUVQoh/u3TpEqqq4u3tnWWapk2bMmnSJPr27Uvp0qXp0KEDn3zyCZGRkRnSNmvWDAcHB+zt7Zk7dy4NGzakXbt2WeYdFhbG+vXrs9xd6MCBA2zcuJHhw4fn/OGEEM+0Tp065WuwB7kM+O7cucO4ceP4/fff+fTTT/n000/Zt28f77zzDvHx8fz2229MnjyZmTNn5mtlhRAiXXZXBJg1axYREREsW7aMWrVqsWzZMry9vTl16pRRuo0bN3L8+HG+//57qlatyurVq7G0tDRKc+rUKRwcHLC1taVJkyb4+fmxePHiDGWePn2al19+malTp9K+ffvcP6QQRZhsrWZectWl++233xIWFpbhfO/evWnYsCFffvklffr0Yd68eXmuoBDCmJWVFatWrdJeF7fysqtatWooisL58+efmrZUqVL07NmTnj17Mnv2bBo0aMDcuXNZs2aNlsbDw4Nq1apRrVo1UlJS6Nq1K6dPnzbaTq5GjRr89NNPWFhYUK5cuUw/j7Nnz9KuXTuGDx/O5MmT8+dhhSiCpEvXvOSqhc/GxoYDBw5kOH/gwAFsbGwAMBgM2mshRP6xtLRk0KBBDBo0KEMLVHEoL7tcXFwICAhgyZIlGWbcAkRHR2d6n5WVFVWqVMn0nnQ9evTAwsKCzz//PMO9VatWxdPTM9Ng78yZM7Rp04aBAwcya9asnD2QEEIUoFy18I0cOZI33niDsLAwGjduDMCRI0dYsWIFkyZNAuDXX3+lfv36+VZRIYR43JIlS2jevDlNmjRhxowZ1K1bl5SUFLZv387SpUv55JNP2LBhA71796Z69eqoqsrPP//Mtm3btFbLzCiKwqhRo5g2bRqvv/46dnZ2T63L6dOnadu2LQEBAYwdO5aIiAgA9Hp9rve+FKIoUwFDPuQhTCNXAd/kyZPx8vJi8eLFfP3110BaV8eXX35J3759AXjjjTd4880386+mQgggbauzX3/9FYCAgACTbK1myvJyonLlyhw7doxZs2Yxbtw4bt26haurKw0bNmTp0qVUrFgROzs7xo0bx/Xr17G2tqZatWqsWLGCV1999Yl5Dxw4kPfff5/FixczYcKEp9blu+++IyoqirVr17J27VrtfKVKlQgPD8/rowpR5EiXrnlRVNkLjdjYWJycnIiJicn3WTFC5Lf4+HgcHByAtK3OMluSxJzLy8qjW7cJ/3wdd/ccxNLZkQqvdqVsj0AUXa5GpghRrJjydyy9rO2Hr2PvkLey4uNieaGJh/z+mkCe/lQPCwvj3LlzQNpCpw0aNMiXSgkhxL8l/H2d/c17knQ/BlINoNMRFbKPOzv3U2fZf7K1vp4QIn/JXrrmJVcB3+3bt+nduzd79uzRVn2Ojo6mTZs2bNiwQcarCCHy1fnJn5J8PzYt2AOSU1PRA9dXfkeFAd1wad6wcCsoxDNIunTNS676QkaOHMmDBw84c+YM9+7d4969e5w+fZrY2FhGjRqV33UUQjzDVFUlYssO1NRUADYY7tI39TJfGG6jWFgQ+dOOQq6hEEIUfbkK+EJCQvj888/x8fHRztWsWZMlS5bwf//3f9nOZ9++fbz44ouUK1cORVHYsmWL0XVVVZkyZQply5bF1tYWf39/Ll68aJTm3r179OvXD0dHR5ydnRk6dChxcXG5eSwhRJH1v6HGFih0UZzppSuVdsXwzA9DFqJQyMLL5iVXAZ/BYMh0PS5LS0sMhuxP0o6Pj6devXosWbIk0+sff/wxCxcuZNmyZRw6dAh7e3sCAgJ49OiRlqZfv36cOXOG7du3s3XrVvbt2ydbGQlRjCiKQplObVD0egB66Fzopy+Ni2KBmpKC24uZb20mhChYBjV/DmEauQr42rZty9tvv83Nmze1czdu3GDMmDFP3HvycR06dOA///kPXbt2zXBNVVUWLFjA5MmTefnll6lbty5fffUVN2/e1FoCz507R0hICCtWrMDX15cWLVqwaNEiNmzYYFQ3IYR58541Dn0Jey3oQ5fWKlCud2dcnm9ciDUTQgjzkKtJG4sXL+all17C09MTDw8PAK5fv07t2rWN1p/KiytXrhAREYG/v792zsnJCV9fX0JDQ+nduzehoaE4OzvTqFEjLY2/vz86nY5Dhw5lGkgCJCYmkpiYqL2PjY3NlzoLYQpWVlba/q2m2lrNlOVlxqG6Fy3DfuTKZ6u5sysUy5KOVBjYnQr9X5YZukIUEpmla15yFfB5eHhw7NgxduzYoe1j6ePjYxSc5VX6KvVubm5G593c3LRrERERlClTxui6hYUFLi4uWprMzJkzh+nTp+dbXYUwJUtLS4KCgopteVmxrViOmp9OKuxqCCH+S2bpmpdcr8OnKAovvPACL7zwQn7WxyQmTpzI2LFjtfexsbFaS6UQQgghRHGT7YBv4cKF2c40P5ZmcXd3ByAyMpKyZctq5yMjI7U9et3d3bl9+7bRfSkpKdy7d0+7PzPW1tZYW1vnuY5CFIbU1FR+//13AJ5//nn06ePaikl5QgjzoKppR17zEKaR7YBv/vz52UqXvul4Xnl5eeHu7s7OnTu1AC82NpZDhw5pe/T6+fkRHR1NWFgYDRumLby6a9cuDAYDvr6+ea6DEEXRo0ePaNOmDWCarc5MXZ4QwjwYUDDkcQxeXu8X2ZftgO/KlSuZnv/jjz9o1KgRNjY2OS48Li6OS5cuGZVx4sQJXFxcqFixIqNHj+Y///kP1apVw8vLiw8++IBy5crRpUsXIG3cYGBgIMOGDWPZsmUkJyczYsQIevfuTbly5XJcHyGEEEKI4ijPu4537Ngx10ugHD16lAYNGmh78I4dO5YGDRowZcoUACZMmMDIkSMZPnw4jRs3Ji4ujpCQEKPgct26dXh7e9OuXTs6duxIixYtWL58eV4fSwghhBBPkD5pI69HQcnNxgyPHj0iKCiIUqVK4eDgQPfu3YmMjNSunzx5kj59+uDh4YGtrS0+Pj589tlnRnns2bMHRVEyHE+aTGoKeQ741Dx0wLdu3RpVVTMcq1evBtK6h2fMmEFERASPHj1ix44dVK9e3SgPFxcX1q9fz4MHD4iJiWHlypU4ODjk5ZGEEEVUZl+i/z6mTZtGeHg4iqJw4sQJAO29Xq/nxo0bRvndunULCwsLFEUhPDzcKH36UapUKdq3b8/x48e1+6ZNm4a3tzf29vaULFkSf39/Dh06ZKqPQYgiIX0MX16PgpKbjRnGjBnDzz//zKZNm9i7dy83b96kW7du2vWwsDDKlCnD2rVrOXPmDO+//z4TJ07Ulq76twsXLnDr1i3teHxVEVPL9SxdIYQwtVu3bmmvN27cyJQpU7hw4YJ2zsHBgTt37mR6b/ny5fnqq6+YOHGidm7NmjWUL1+ea9euZUi/Y8cOatWqxT///MOoUaPo0KED58+fx9nZmerVq7N48WIqV67Mw4cPmT9/Pu3bt+fSpUu4urrm4xMLIXIjfWOGI0eOaGv1Llq0iI4dOzJ37txMh33FxMQQHBzM+vXrads2bQefVatW4ePjw8GDB2natClDhgwxuqdy5cqEhoayefNmRowYYXStTJkyODs7F8wD5kKeW/i++OKLDGvlCSFEQXB3d9cOJycnFEUxOvek1v2BAweyatUqo3OrVq1i4MCBmaYvVaoU7u7uNGrUiLlz5xIZGam14vXt2xd/f38qV65MrVq1mDdvHrGxsfz555/597BCFHH5uZdubGys0fHvzRFy42kbM2QmLCyM5ORkozWFvb29qVixIqGhoVmWFRMTg4uLS4bz9evXp2zZsrzwwgvs378/D0+TP/Ic8PXt21dm7QkhiryXXnqJ+/fv88cffwBpE87u37/Piy+++NR7bW1tAUhKSspwLSkpieXLl+Pk5ES9evXyt9JCFGH5uZeuh4cHTk5O2jFnzpw81S03GzNERERgZWWVoVXu3xs+PO7AgQNs3LjRqKu4bNmyLFu2jO+//57vv/8eDw8PWrduzbFjx/L0THklXbpCmBlLS0s+/vhj7XVxK6+gWFpa0r9/f1auXEmLFi1YuXIl/fv3f+ozRUdHM3PmTBwcHGjSpIl2fuvWrfTu3ZuEhATKli3L9u3bKV26dEE/hhDF0vXr13F0dNTeZ7VW7nvvvcdHH330xLzOnTuXr3XLyunTp3n55ZeZOnUq7du3187XqFGDGjVqaO+bNWvG5cuXmT9/Pl9//bVJ6pYZCfiEMDNWVlaMHz++2JZXkIYMGUKzZs2YPXs2mzZtIjQ0lJSUlEzTNmvWDJ1OR3x8PJUrV2bjxo1Gw1fatGnDiRMnuHPnDl9++SWvvPIKhw4dKvSB2UKYTH7Msv3v/Y6OjkYBX1bGjRvHoEGDnpimcuXKudqYwd3dnaSkJKKjo41a+SIjIzPcc/bsWdq1a8fw4cOZPHnyU+vdpEkTrXehsEjAJ4R4ZtSpUwdvb2/69OmDj48PtWvX1mbzPm7jxo3UrFmTUqVKZTrw2t7enqpVq1K1alWaNm1KtWrVCA4ONpoUIkRxVhg7bbi6umZrYlRuNmZo2LAhlpaW7Ny5k+7duwNpM22vXbuGn5+flu7MmTO0bduWgQMHMmvWrGzV+8SJE0a7hhUGCfiEMDOpqanaWJDnnnvOJFurmbK8gjZkyBDeeustli5d+sR0Hh4eVKlSJdv5GgyGPA80F0Lkj+xszHDjxg3atWvHV199RZMmTXBycmLo0KGMHTsWFxcXHB0dGTlyJH5+fjRt2hRI68Zt27YtAQEBjB07Vhvbp9frtUB0wYIFeHl5UatWLR49esSKFSvYtWsXv/32W+F8GP8lAZ8QZubRo0faWDJTba1myvIK2rBhw+jZs2eul0uIj49n1qxZvPTSS5QtW5Y7d+6wZMkSbty4Qc+ePfO3skIUYUV9a7V169YxYsQI2rVrh06no3v37ixcuFC7npyczIULF0hISNDOzZ8/X0ubmJhIQEAAn3/+uXb9u+++IyoqirVr17J27VrtfKVKlbS1PJOSkhg3bhw3btzAzs6OunXrsmPHDm2LysIiAZ8Q4pliYWGRp8kVer2e8+fPs2bNGu7cuUOpUqVo3Lgxv//+O7Vq1crHmgpRtBVGl25OpG/MkBVPT88Mm0fY2NiwZMkSlixZkuk906ZNY9q0aU8sd8KECUyYMCHH9S1oipqXrTKKidjYWJycnIiJicnWoFEhClN8fLy23pwpWtxMXd6/paaqfL/1Bpt/ucGde0lUr+LAwF6V8H0u45pXQjzLTPk7ll7Whj13sXPIW1kJcbH0bl1Kfn9NIM/r8AkhREH5ePFfLFxxmX9uPeJRooHT52MZN/UUO3+//fSbhRAFqqjvpSuMScAnhCiSwq/H88uO/y12akhN5FHCXQCWrPwbg+GZ75wQolDl58LLouBJwCeEKJKO/RmtDed+GP8PR3b05M/9Qaiqyu07idyKfFSo9RNCCHMikzaEEEWSjbWe9D/+La2c8ag2gJJuTVGUtDDQxsa8l4cRwtwV9UkbwpgEfEKYGUtLS6ZOnaq9LqrlqampGBKT0NnaaEFaTrRoWgrLzxWSk1UsLB0oV7kHADod1PFxolRJqxznKYTIPyoKah6XVcnr/SL7JOATwsxYWVk9dVmAwiwvJT6Bv6Ys4Frwt6TGP8SuaiWqTx1F+d6dc1Suo4Mlk972Zuan51AUUElrDXAsYcm7I6rn7CGEEOIZJwGfECLfqKrK0W5vcXfvIUg1AJBw+RonXh2HmpJChf5dcpTfC63KUKOKA7/siEhblqWyAx383XB0KPiWTSHEkxnI+6QLQ77URGSHBHxCmBmDwcC5c+eAtO2DdLqCnXuVk/Lu7w/j7q5Q45P/HaRz4YP5lO/7EkoO61uxgh1vDqqcs0qLYk81GLj3+xESI+7gWN8Hhxryb8TUZAyfeZGATwgz8/DhQ2rXrg2YZiHknJR3/+Bx0Osg1cBF9RFzU2/RSLFnkM4V/okg8VYUNuXdCrS+ovh7cOYiR7u9ScLf17Vz7l3bU3/NJ+htbQqxZkIUXbIsixAi31iWdNa6cj2wwldx4Kz6kBhSUPQ6LBzNex9eUfgMSUkc6jiEh1dvGp2P+HEH5979qJBq9WxKb+HL6yFMQwI+IUS+KdutPTpba1AUbBQdQ/SuzLeohKuFDW5d2mNRwqGwqyjMXOQve0i8eRs1NdX4gsHA9ZXfkRKfUDgVewYZVCVfDmEaEvAJIfKNZUknnls3H8XSAnRK2v8C9tU9qf3ZB1q6+6HHOfXWFMJ6j+LvBatJjo4trCoLM/Mw/Eba2jyZMCQmkRR1z8Q1EsI8SMAnhMhXbi+2o93fe/D56D0qjx7McxsX8nzYj1i7lSYiIoIBzdvg08yX55b+h8CNS+k9dgQLajTn4bWbnDx5kpdeeokyZcpgY2ODp6cnvXr14vbttL1zw8PDURRFO1xcXGjVqhW///67UR2mTZumpbGwsMDT05MxY8YQFxenpRk1ahQNGzbE2tqa+vXrm/IjEnngULMKGDKf26l3sMfa3dXENXp2SZeueZFJG0KIfGftVprKowcZnQsPD6eZb1Msb99niK40noo1KagcUxNYGPUXDUZNpfcfP9C5c2d+/fVXnJ2dCQ8P56effiI+Pt4orx07dlCrVi3u3LnDrFmz6Ny5M3/99Rdubv+bEFKrVi127NhBSkoK+/fvZ8iQISQkJPDFF19oaYYMGcKhQ4f4888/C/TzEPnH1b85Dj5ViL8Yjpryr25dRcFr1AD0NtaFV7lnjMzSNS8S8AkhTOKtt97C8CiR+VZeWP9r8a5KijUvqI7s/SWEGGJYsWIFFhZpX01eXl60adMmQ16lSpXC3d0dd3d3Jk2axIYNGzh06BAvvfSSlsbCwgJ3d3cAevXqxc6dO/npp5+0gG/hwoUAREVFScBnRhS9Ht//W8Xxge9wb+/htHNWlngG9af6lJGFXDshii4J+IQwM5aWlrzzzjvaa3Mo7969e4SEhDC6TUdsDvyNajAecO+g6HFWFVJSU/jhhx/o0aNHtrZje/jwIV999RWQtiPIk9ja2pKUlJSr+ouixaa8G347vibh7+s8ioiihE8VLEs6FXa1njmqmveFl6WFz3Qk4BPCzFhZWfHJJ5+YVXmXLl1CVVXqt2uFuu9ixgQ6HX5NmzOpRWX69u3LG2+8QZMmTWjbti0DBgww6qoFaNasGTqdjoSEBFRVpWHDhrRr1y7L8sPCwli/fj1t27bN03OIosWusgd2lT0KuxrPLFVVUPM4yzav94vsk0kbQogCp/73z3gH7yq4vewP/2q9U/R6FL0O79nvMGvWLCIiIli2bBm1atVi2bJleHt7c+rUKaP8Nm7cyPHjx/n++++pWrUqq1ev1lofH5y9RNRvf3Dqzz+xt7bB1taWJk2a4Ofnx+LFi0330EIIUYRIC58QZsZgMHDt2jUAKlasaJKt1fJaXrVq1VAUhQsXLtDlmwWEL/6aa8Hfknw3mpItGlHtvTdwapi2m0epUqXo2bMnPXv2ZPbs2TRo0IC5c+eyZs0aLT8PDw+qVatGtWrVSElJoWvXrpw+fZo73//KicHvEp16h/KqJR+o5bGytafTH2sp3bBu/nwgQghAJm2YG2nhE8LMPHz4EC8vL7y8vHj48KFZlOfi4kJAQABLlizhYVISlccMofXpEF64dZBGmxajVqmQ6X1WVlZUqVIlwyzdf+vRowcWFhYs+nQef74+GQwGVIMBCxTKqRa4JqRwfuTMXNVbCJE1g5o/hzANCfiEECaxZMkSUlNTadKkCd9//z0XL17k3LlzLFy4ED8/P7Zu3Ur//v3ZunUrf/31FxcuXGDu3Lls27aNl19+Oct8FUVh1KhRfPTRRyRkEpCqqanEHPmTh9dvGZ2/dOkSJ06cICIigocPH3LixAlOnDghEzuEEMWSdOkKIUyicuXKHDt2jFmzZjFu3Dhu3bqFq6srDRs2ZOnSpVSsWBE7OzvGjRvH9evXsba2plq1aqxYsYJXX331iXkPHDiQie+MZ6saTQ/FJdM0qQnGweBrr73G3r17tfcNGjQA4MqVK3h6eubtYYV4BkiXrnlRVFU+7tjYWJycnIiJicHR0bGwqyPEE8XHx+PgkLYnbVxcHPb29sWqvNxK+Ps6u71fyPQXxKa8O20v70LR6wuhZkIUPFP+jqWXtfinGGzt81bWw/hYRrwkv7+mIF26Qohiwa6yB5Xe6pf2Jn0WsF4HikLNue9JsCeEeKZJl64QotioNe99StSsRvjna3l0IxKn+j5Ufe8NSrdrVthVE6LYyY9JFzJpw3Qk4BNCFBuKTkel4b2pNLx3YVdFiGJPxvCZFwn4hDAzFhYWvPXWW9rr4lZeTj04c5HLn67gfuhxrN1LU/G1XpTv+1K2tmYTQohnRdH79hZCPJG1tTVLliwptuXlxL0DxzjUfiBqaipqSioJf1/n/h9hRB8+Se3PphR29YQo1gyGtCOveQjTkEkbQgizdXbcbAzJKagpqWkn/vvrcfXzdTw4e6kQayZE8ZfepZvXQ5iGBHxCmBlVVYmKiiIqKgpTrKpk6vKyK+leNDFHT2XeRKDTcXvbbtNXSgghiijp0hXCzCQkJFCmTBnANOvimbq87FKesqevopevNyEKkkzaMC/SwieEMEuWzo64tGyCos/ka0xVcX/Z3/SVEuIZYiAf9tIt7Id4hkjAJ4QwW7UWTEZvb5e2wDJoiytXnzoSu8oehVk1IYQoUqTPQwhhthzr1KDlyV+4unQd9w+eSFuWZUhPWWhZCBNQVTXP43qL0rjg4k4CPiGEWbOt4I73rHGFXQ0hnjkyhs+8SJeuEEIIIUQxJy18QgghhMgxNR8WXlZl1obJSAufEGbGwsKCgQMHMnDgQJNtrWbK8oQQ5qGoL7x87949+vXrh6OjI87OzgwdOpS4uLgn3vPo0SOCgoIoVaoUDg4OdO/encjISKM0iqJkODZs2GCUZs+ePTz33HNYW1tTtWpVVq9end+Pl2Py7S2EmbG2tjbpl4epyxNCiPzQr18/bt26xfbt20lOTmbw4MEMHz6c9evXZ3nPmDFj+OWXX9i0aRNOTk6MGDGCbt26sX//fqN0q1atIjAwUHvv7Oysvb5y5QqdOnXijTfeYN26dezcuZPXXnuNsmXLEhAQkO/PmV0S8AkhzEbsn+e5u+cQegc73F/2x6pUycKukhDPrPS19PKaB0BsbKzReWtra6ytrXOd77lz5wgJCeHIkSM0atQIgEWLFtGxY0fmzp1LuXLlMtwTExNDcHAw69evp23btkBaYOfj48PBgwdp2rSpltbZ2Rl3d/dMy162bBleXl58+umnAPj4+PDHH38wf/78Qg34pEtXCDOjqirx8fHEx8ebbGs1U5aXGUNKCscHvMPvDV/m7Pg5nHp9MjsqPs+Nb34ulPoIIfK3S9fDwwMnJyftmDNnTp7qFhoairOzsxbsAfj7+6PT6Th06FCm94SFhZGcnIy///8Wbff29qZixYqEhoYapQ0KCqJ06dI0adKElStXGn03hoaGGuUBEBAQkCEPU5MWPiHMTEJCAg4ODoDptlYzZXmZubJgFTc3bE17898mATUpmRODJuDcqA721TxNXichRP65fv06jo6O2vu8tO4BREREaFtCprOwsMDFxYWIiIgs77GysjLqngVwc3MzumfGjBm0bdsWOzs7fvvtN9566y3i4uIYNWqUlo+bm1uGPGJjY3n48CG2trZ5erbckoBPCFHkXV32TaajuxVF4fpXP+A9c0wh1EqIZ5tqUFHz2Kebfr+jo6NRwJeV9957j48++uiJac6dO5enOj3NBx98oL1u0KAB8fHxfPLJJ1rAV1RJwCeEKPISI+9kfkGBxFu3TVsZIQSQv2P4smvcuHEMGjToiWkqV66Mu7s7t28bfzekpKRw7969LMfeubu7k5SURHR0tFErX2RkZJb3APj6+jJz5kwSExOxtrbG3d09w8zeyMhIHB0dC611DyTgE0KYAafnanH/4IkMi36pqQacGtQqnEoJIUzO1dUVV1fXp6bz8/MjOjqasLAwGjZsCMCuXbswGAz4+vpmek/Dhg2xtLRk586ddO/eHYALFy5w7do1/Pz8sizrxIkTlCxZUuuG9vPzY9u2bUZptm/f/sQ8TEEmbQghiryqk97M0KWr6PVYu5em/KtdCqdSQjzjivI6fD4+PgQGBjJs2DAOHz7M/v37GTFiBL1799Zm6N64cQNvb28OHz4MgJOTE0OHDmXs2LHs3r2bsLAwBg8ejJ+fnzZD9+eff2bFihWcPn2aS5cusXTpUmbPns3IkSO1st944w3+/vtvJkyYwPnz5/n888/59ttvGTOmcIeeSAufEKLIKxPQkue+WcC5dz/m4dUbAJRq7UvtJdOxdHQo5NoJ8WwyGFQMeezTzev9T7Ju3TpGjBhBu3bt0Ol0dO/enYULF2rXk5OTuXDhAgkJCdq5+fPna2kTExMJCAjg888/165bWlqyZMkSxowZg6qqVK1alXnz5jFs2DAtjZeXF7/88gtjxozhs88+o0KFCqxYsaJQl2QBUNTCWmchG6ZNm8b06dONztWoUYPz588DaStijxs3jg0bNhj9h3l8dszTxMbG4uTkRExMTLYGjQpRmOLj4006a9bU5T2JajDw6J8I9Pa2sgafEP9iyt+x9LKmrLqHjV3eynqUEMuMwS7y+2sCRb6Fr1atWuzYsUN7/++tnbK7IrYQxYler6dHjx7a6+JW3pMoOh22FTMumCqEML386JItuk1OxU+RD/gsLCwynR2TkxWxhShObGxs2LRpU7EtTwhhHiTgMy9FftLGxYsXKVeuHJUrV6Zfv35cu3YNyNmK2I9LTEwkNjbW6BBCCCGEKK6KdMDn6+vL6tWrCQkJYenSpVy5coXnn3+eBw8eZHtF7MzMmTPHaAsXDw+PAnwKIYQQovgxqGq+HMI0inSXbocOHbTXdevWxdfXl0qVKvHtt9/mafHCiRMnMnbsWO19bGysBH3CbDzLkzaEEELkTpEO+B7n7OxM9erVuXTpEi+88EKuVsSGtD368rpPnxBCCPEsUw1pR17zEKZRpLt0HxcXF8fly5cpW7as0YrY6bKzIrYQQggh8k5FRVXzeCBduqZSpFv43nnnHV588UUqVarEzZs3mTp1Knq9nj59+hitiO3i4oKjoyMjR440WhFbCCGEEEIU8YDvn3/+oU+fPty9exdXV1datGjBwYMHtX30nrYithBCCCEKhmrIsL11rvIQplGkA74NGzY88bqNjQ1LlixhyZIlJqqREEIIIQCtWzaveQjTMKsxfEIIIYQQIueKdAufEHmhGgwouuL3N41er6djx47aa3MsLyU+gevBm4jcugvFQk/ZboGUf7ULemurfMlfCFHwDGrakdc8hGlIwCeKldTEJC7N/pyrX3xD8t1oHGpVo/oHIyjbPbCwq5ZvbGxs+OWXX8y2vJQHcRxo3ZcHp/7Szt3Zvp8b3/yM7/8Fo7OSoE8Ic6AaVNQ8Rmx5vV9kX/Fr/hDPtOP9xnDpwy9IvhsNQNzZSxzr/Tb/rN1SqPUS/3Nl8dc8OH3xfxtx/ncMz719h/nn6x8LuXZCCFE8ScAnio2YsNNE/rjDeNrYf4OJ8+/PQ01NLaSaiX+79V1I5lP7FIWIzb+avkJCiFz5999seTmEaUjAJ4qNe38cBZ2S6bXEm5E8vH7LxDUqGPHx8djb22Nvb098fLzZlfekwNsgQbkQZsNgUPPlEKYhAZ8oNiycSmQ9AlhRsChRfPaATUhIICEhwSzLc3/ZH/SZf/W4v9guX8oQQghhTAI+UWy4d3kBna01KMatfIpej2tgS6xKlSykmj3bUhMeYkhO1t57vT0IO88KxkGfTodjfR88BncvhBoKIXIjz9uq5cM6fiL7JOATxYalsyMNvp6HYqEHvQ7FMm0Suk0Fd+osmV7ItXv23NlzkD/8ehDiVJ8Qx3oc6zeWRzcjsXJxpvmBTVSb+CYl6tTAsb4PNWaOwW/XWvR2toVdbSFENqmG/DmEaciyLKJYcX/Zn7YXd/HPuh9JvHUbpwa1KNuzA3pbm8Ku2jPl3v4wDncYoi25oKakErE5hOjDJ2l5/CesXJypPnUU1aeOKuSaCiHEs0ECPlHs2JR3o+qE4YVdjWfaxdmfp82++9dsXDUllYdX/+HG+p+pNLx3nvJPSVUJO3mfqLuJVK/sQPUqJfJYYyFEThlUFUMeu2Tzer/IPgn4hBD57v7+Y5DJjFtFp+d+6PE8BXyXw+MYP/00t+8kauca1y/JrIk1sbOTrzQhTEX20jUv8u0ohJnR6XS0atVKe10Uy7N0cSI1PpNZvQpYlXLOdV2Skw2Mm3qKe9FJRufD/rzPvGWXmDzWO9d5CyFEcSaTNoQwM7a2tuzZs4c9e/Zga1vwkxxyU17FIT0yXRNRTUmlfP8uua7LwbB73LmXlGHdZoMBtu+9zYO4lFznLYTIGVmHz7xIwCeEyHeVxw/H9YXnAbRZ0ygKNT+dhFN9n1zne/tO4uOr7mhSDSr3Y5IyvyiEyHey04Z5kS5dIYqIpDv3ePhPJHae5bF0dizs6uSJ3tqKxj8v5+7eQ9zdFYre3o5yPTtiV9kjT/l6VbLP8gfC1kaHW2nrPOUvhBDFlQR8QhSylLh4To+Yzo0NP0OqAcXSAo/BPag573301lYZ0sfHx+Pp6QlAeHg49vYFu4NIbstTFIXSrZtSunXTfKtLg9pO1KjqwKW/40h9rFu318sVsLbW51tZQognU1VVW3opL3kI05AuXSEK2YkB47VgD0BNTuHaio2cHjEty3vu3LnDnTt3TFRD05eXFUVRmDutDk0bldLOWVnpeLWnB4P7eBZexYR4Bqn/XZYlL4cEfKYjLXxCFKK4v64Q+fPOjBcMKv98/QM1Zo7Bxt3V9BUrwko6WfHRB7W5cy+Re/eTqFDWVpZjEUKIp5BvSSEK0YMzF7O+mGog/sLfEvBlobSLNaVdZMyeEIVFNeRDl67M0jUZCfiEKES25d2feN3mKdeFEKKwSMBnXmQMnxCFyKlxHUrU9U5buuRfFAs9pdo0xb5qpUKqmRBCiOJEAj4hCpGiKDT6fgn2VT2Nzpeo4039r+YWTqWEECIbDGr+HMI0pEtXiEJm51mBlie3cnffYRL+vo5DjcqUbPYcShYrDOt0Oho1aqS9LmimLk8IYR6kS9e8SMAnRBGg6HRp69VlY806W1tbjhw5YoJaPb286MN/cmXRGuLO/419dS88g/rj0uw5k9VNCCFE9kjAJ4TIlZubtnG831gUvQ41JZUHpy9wa9M26q38kAr/2i9XVVXu/XGUh1f+wcG7Ck6N62TZeimEMB9qPqyjJ+vwmY4EfEKIHEtNTOJ00DRQVdSUVADtf8+MmknZbgHo7WxJCP+HIy+9Tty5S9q9Jf2eo9HmJViVdimMqgsh8onBAIY8dskaDE9PI/KHDMgRwswkJCTg6emJp6cnCQkJhVJe9KETJN+PyTR9yoM47u0PQ1VVjnZ9k/iLV4yuRx8+yYnB7xZ4vYUQz7Z79+7Rr18/HB0dcXZ2ZujQocTFxT3xnkePHhEUFESpUqVwcHCge/fuREZGatdXr16NoiiZHrdv3wZgz549mV6PiIgo0Od9GmnhE8LMqKrK1atXtdemLO/ACwMo69sA58Z1n3pf9KGTPDj9V8b8UlOJCtlHwtUb2FUqn+/1FUKYRlHv0u3Xrx+3bt1i+/btJCcnM3jwYIYPH8769euzvGfMmDH88ssvbNq0CScnJ0aMGEG3bt3Yv38/AL169SIwMNDonkGDBvHo0SPKlCljdP7ChQs4Ojpq7x+/bmoS8Akhnujvz1Zpr2MOnSQp7CxXLTdiUcKelAfxGdJblHDApXlDIrfufmK+j67fkoBPCDNWlGfpnjt3jpCQEI4cOaKtMrBo0SI6duzI3LlzKVeuXIZ7YmJiCA4OZv369bRt2xaAVatW4ePjw8GDB2natCm2trbY2tpq90RFRbFr1y6Cg4Mz5FemTBmcnZ0L5PlyQ7p0hRBZenQjkr+mLTI6p6amoiYlY+niDIqSdoD2vxXf6IPO1oYStaplnbFeh311rwKqtRDC3MTGxhodiYmJecovNDQUZ2dnLdgD8Pf3R6fTcejQoUzvCQsLIzk5GX9/f+2ct7c3FStWJDQ0NNN7vvrqK+zs7OjRo0eGa/Xr16ds2bK88MILWgthYZKAT4gCpKoq19dsZl+DFwlxbsAfvt24uWlbYVcr2yJ/2Q2ZdbkYDDy8egNdCfv/XVdVUODvT77kz2GTcKhZFdf2LVD0xruIoFPwGNgd6zKlCv4BhBAFJr2FL68HgIeHB05OTtoxZ86cPNUtIiIiQxeqhYUFLi4uWY6li4iIwMrKKkOrnJubW5b3BAcH07dvX6NWv7Jly7Js2TK+//57vv/+ezw8PGjdujXHjh3L0zPllXTpClGALv5nCRdnLEpr/VJVYk6c5XjfMSTeisJr1MDCrt7TPWUKnSH2sQHQ/439/lmzGbfObWmwfgGn3vyAW9+FgKqiWFjgMbg7NedPLqAKCyFMxYCKIY9j8Az//dK4fv260Xg3a2vrTNO/9957fPTRR0/M89y5c3mqU3aFhoZy7tw5vv76a6PzNWrUoEaNGtr7Zs2acfnyZebPn58hrSlJwCdEAUm6c49Lc5amvUn/UvzvX7MXpi7AY2hPLOzt/r+9Ow9r4lr/AP6dJIQk7AKCKCBYFFEUBEHEKhZXbG/dtWrr9qPXVlyqdtVWu+l1KbWltm5Xa3vpVVu7WK56r+JWLWoBtUoVUVEUWazsIGSZ8/sjEk0hkUBCTHw/z5PnITNnzrwn4OT1nJlzzBRd07gP69/4jnsJrE5CAfK3p8Bz5GD0+mYtahNvo/ZmIWR+HSB2ddEUYzwPjlbvIOSx5+joqJXw6bJw4UJMmzZNbxl/f394enpqnpqtp1QqUVJSAk9Pz0aP8/T0hFwuR1lZmVYvX1FRUaPHbN68GSEhIQgLC3to3BERETh27NhDy5kSJXyEmEjJr5lgCmWj+1RVNSjPzILrk70NrpfjOAQFBWl+NiVZxw7o9Or/wWfF20D9rXoi4b0n6zhApaMHUMVDVXX/gQ6Jpzsknu4AAF6hwJVVG3Ft3b8gv10Cu85+eOKtl9Bh8rMmbQshxLjM8dCGu7s73N3dH1ouKioKZWVlyMjI0CRkBw8eBM/ziIyMbPSYsLAw2NjYIDU1FWPGjAGgftI2Ly8PUVFRWmWrqqqwc+fOJg89nzlzBu3atWtSWVOhhI8QE3lY751QKmlWvTKZDFlZWc06VheVikHFM4htGva29fzwVZzoHYK8jdtRe7MQThE94NC1Ey6+uUZ3hQIOrk9FNbrr9/i3kP/Nz5oewuqcazg77TUoK6rQ8aXJRmkPIcT0HuVpWbp27Yphw4YhPj4e69evh0KhQEJCAiZOnKh5Qjc/Px+xsbH46quvEBERAScnJ8ycORMLFixAmzZt4OjoiDlz5iAqKgp9+mgve7ljxw4olUpMmTKlwbnXrl0LPz8/dOvWDbW1tdi8eTMOHjyI//3vfyZpa1NRwkeIibR5Mhxi9zaQ/1mqPfwpEEDq4wWnXt0MrpOXy1H40wFUZuVA6uMFr3HDIXKwb3aMJaVyrNt6Bam/3IZSyRDUxQEvTfVHaLCzpgzHcWg3agjajRqi2aaqk+P6+n/j7o2Chvf5CThIfdrDZ+b4BuerungF+cm7tTfe+2wuLfsEPjPHQSAWN7s9hBBSLzk5GQkJCYiNjYVAIMCYMWPw6aefavYrFApkZ2drTWD/8ccfa8rW1dVh6NCh+PzzzxvU/c9//hOjR49udNoVuVyOhQsXIj8/HzKZDD169MCBAwcwcOBAk7SzqThGC9mhoqICTk5OKC8vb9I9BIQ01e0Dx5E+chZ4pRKA+r43odQWkXu3wiUq1KC6anJv4MTgqbh7PR+cSASmUkLk5IDI/2yBc8TDJ0L+q9paFabNy0BB4V3NyCzHAQKOw2f/6Ingrk6NHif/swQ5H3yOm8k/QVlRpZXwCaQSdHhhFDq/nQBbD7cGx+Zt+Rbn/q77gY3+p3+GQ/fOBreFkMdda36P1Z9r/MKLsLF1aFFdirpK7PwokL5/WwH18BFiQu6DohHzx39x48tdqLmSB7tAf3hPGwNJO8NnXD8z/XXU5heilvFYUKtemzaxvCPSx7yMp64egsDGxqD69h8pxs1bd7W2MQYwjmHLN9fx8fvqJLKmpga9e6vvNUw7fASZMVNQcyUPTKVeOxdCAYS2YvQ5lIyay3ko2LUPv896G22HPokOL4yCUHZ/ugIbZ/0XdJFTy748CCGt51GeeJk0RAkfISYm9fFC53fmtKiOmtwbKD2eoXmfB7n6B55HXeFt3Dl0Au5DnjSoznMXKyAUclCptC+4PA+cu3B/nVzGGP744w8AwM3kn1Cdc017iFrFg69TIGNsAmpvFAACAcAYiv9zENc370DUwWTYOKqHndsO6w+Rk4O6Z/CBOjihEM5RoZB6m/emZkIIsVY0HwIhFkD+Z6ne/XW3Swyu08Fe9//37O0a31fyS3qj25lKpU72AHXGyBjAgMpzl5D78RZNOaFMil7/XguBrRgQCMDZqM9j6+mGnptbNtEqIaR11T+00dIXaR3Uw0eIBbDv2glCmQSqmtpG97tE9DS4zmFPeWDHjzcbbBdwwNODG5+nSiSTghMKwJSqpp2E53FrRwo6L52r2eQ+uB+eunwQN5N/Qu3NQjgGd0G78XGP/JyEhBBtjOfBHjI5e1PqIK2DevgIsQAiezt0eu3FhjsEHLyeexp2AR0NrjPAzx5z/68TOKhHYYVC9UR7oT2c8fw4n0aP8Rw3vOnJ3j18naLBNlsPN3RaMBPdEhfDe/pYSvYIIcTEqIePEAvxxFsvQ2Rvh3MrvwDujZ76zZuGnh8uanad45/tgKjebZD6y23cvatCWA9nhIe4QCBofEJnt6ei4Dt7Cq6v+xc4kXqNXKZUQdbJBzVX8hqU54RCePwtttnxEUIeXTzPwLfwoYuWHk+ajhI+QiwEx3HwmzcN7jPGAPemL+iybF6L563z9pJh2gRfzXvV3Vpc+3IXilMOAgIBHOPuL6/GcRy6fbwE7cYMQ8G3e8HXyeE+pB/chvTDidjnUXH2omaaFk4ohNjdBZ0WxbcoPkLIo+lRnniZNEQJHyEWRiAUwtdXnaAZe2k1ZXUNTsQ+j/LM+yt53Nh7GJ4SO828eqUnTuP2vqOQ+nVA+wkjIPHyAABEpX6N3E++RP72FPB1Cng88xQ6Lfw/SNp7GDVGQgghhqOEjxALI5PJcO3aNZPUff2LZJSfztKaMkXCCbBZ2R7dXn8HGdETUJmVo9l38fVV6PbJ2+j40mSIHOwRsCQBAUsSjBoTL5cDAgEEIrpcEfIooXn4LAs9tEEI0bi1cw+g4wJ88c3VWskeAIAxZM19r+F2IyhNO41fYyZhr10w9jn2RObkBbh7s9Do5yGENE99wtfSF2kdlPAZCa9U4srqjUjt2B97pEE4GvYsCr7/r7nDIsQgvFyuc5+q+q7OfVcTt+jc1xzlmVlIG/Q8Sk+cBgAwhRKFu/bh1/4ToSivNOq5CCHkcUAJn5Gc+/sSXFyciNr8IjClCpXnspE5YS5ufLnL3KERK3P37l307t0bvXv3xt27upOw5hC7ODfYVsd4vKK8jleU11HHGp8zq/ryNaPGkbPiC0DFQ7PIL+5N7nyzEDe3fW/UcxFCmocHD5618AWah6+1UMJnBFUXr+DmVz9oLzd17+eLiz8Cr1SaKTJijXieR3p6OtLT03Hh7Y9x818/omDXPhzvNx77nENwuNswXPs8uVkTmjY2ZMoA5KAOOaiDrsEXhx5dDD6XPqXH0u+v1fsgDihNyzTquQghzcN4YwzrmrsVjw+6C9oIdC03BQDy4juozrkOh66dWjGixjHGUJGZBUV5JZxCg2Dj4mTukEgzlJ48q/n52rqvUaC8d8UUcADPUJ1zDVnz3kN1Ti66fbykSXUylQqKsgrwioaTJD+UQIAu771i+HF62Lg4NbqcHCcQ0N8tIYQ0AyV8RiB0sNO7v37h+NbEGEP5b+cgLymFU6/uqCu4jczn5qkXvgcgsBWj06vxCHhnjtGn9iCmwysUOP38As17plAC3L2O+vqbn+/1Ll9b9y/4zZsGWccOOutjjCF37VZcWb0J8tsl6iU3DMDZiBC2MwliIydh3jPH4eKba7R7zaGe5LnD86MMrk/+ZwlufLkLFWcvQtLBE97Tx8K+s5+xwiXksURP6VoWSviMwGNEDIR2UvU6pw98QXFCIZyjQlt9HrKKe/cP1id3EKqntHhwaJmvkyPng3UQu7ui48uTWzU+S6Kqk6Pm8nXYODua7Peoqq3D5eWfI2/zTihKymHfPQAecTFwH/IkXPr2AvdAEnbn0AnIi+40rWLGcOfIKb0JX84H65DzXtL9DU0cBnaNiUS7CSPQYdLfIJRJmxaPAfzmvICSY+koTjmkXtGDqXshO783Hy5RoQbVVXEuGydin1c/7MEBHDjkfrwFIV9/BK9xcUaPnZDHBU28bFko4TMCkYM9Qr/+CBkT5oLxPDhOAKZSQezugp4bP2zVWJRV1Tg5ZCrkpeX3N6p48KrGn768smYTJXw65H72NXLeS4Li3mfpGhOJHpuW602gHubOkZPIXvoJyk6cgdDBDh2mjkbl+WzcOXRSk2xVnr2IyrMXcXnFetgFdET495/DPlB9S4D8TplB5xPZ6U7GlJVVuLJ6k/4KOMC2gydw7TIAQCCVIGBRPALeTtBKRPWpLSjG3Wv5kPl7ayZvfhiBWIzw779AydFTuL3/OIRSW7QbM0zzORji9xcXQ1lRqfl8679ezs58E+5D+5ulB54QQlobJXxG4vFMLAZmH8DNr75HbX4RHHsEwmvS31r9y6Tg272N3vukS+2NAjCVCpxQaMKoLM+NL3fhj1c+0NpW8ks6TsQ+jwFZ+yCU2Bpc55+H0nBy2Az1G56HsqwC15K26Zz3DgBqrt7AyeEzMPDSAQhsbOASGQI0dQjeRgSXmEiduysvXAF/t1Z/HQzosnQeMP0YAOCpy6lw8mjbpNMrKqpwbtYSFHy3T93zLRCg/XNPo/u6dyGykz30eI7j4DogEq4DdLfhYWqu56M8/Vyj+/i7tSjecxjtJz7d7PoJeZzxPA++GQ+H/bUO0joo4TMiqXc7BCyebdYYqq/kgbMRqe/tagJbLw9K9v6CMYbLy79ouF2lwt28Wyj4bi86TBlpcL3ZSxLVPzx4gXvI/Sv1U5EU7zkC+0B/VGblwH1IPzjuufrwEyqUSG0XBU4qgUvvYHjPHI+2cTEQOzsi78tduLT0kybFraq5Czc3dc+cyF7//aoPOjP1VRTvPXz/NgeeR/6/U8ArlOiV/HGT62kJVY3+hFbf3IKEEP3oHj7LYjUJ37p167B69WoUFhaiZ8+eSEpKQkREhEF1VFdXQ9hI8iMUCiGRSLTK6SIQCCCVSptVtqamRuf9DBzHQSaTPbQs16Et7srlkHD3h9vqGK9zOg3flyZpvb97967e/3HZ2d3/wq+trYWqsakzmlFWJpNpHh6pq6uDUs9UNoaUlUqlENwbepTL5VDoeQq1vixfJ0f51TyoGvnUOBsRijLOod1zz2j+Vh5Wr0QiAccYyk79DiVjUOr8bQA24CC817YHy56csQjK8vt/S197hkFYUwfUqBMWFWNQ6KiX1dRAceQUSo7+BhUnRKnEBfY1xTpjEIGD6F4MKsbgEhWqtZTbg3/TNjY2EIvF6rIqFWpr1QlW9eXryPv5gFa9QnCw4XkUfLsX1csXAW7Ouj+HB+rleV7vfIMikQi2tuoeV8YYampq7u/0cgPftg3kRX/eiwGwufdvgwGQRvbQ+W/UkH/3lnSNaKysIf/u6RrRtLISicSga0R9WYVCAbmeCdBtbW0hurfM4INl9f0dEQIAYFZg+/btTCwWsy1btrCsrCwWHx/PnJ2dWVFRUZOOLy8vZ1Bf/xt9xcXFaZWXyWQ6yw4YMECrrJubm86y4eHhWmV9fX11lg0KCtIqGxQUpLOsh1DMUmwDWYqoM0sRdWYBsNVZ1s3NTaveAQMG6Cwrk8m0ysbFxen93B40duxYvWWrqqo0ZadOnaq3bHFxsabsyy+/rLdsbm6upuyiRYv0lj1//jxjjDGe59lkaTu9ZU+dOqWpd9WqVXrLHjp0iPEqFdtjH8xmCdrqLbtU4KX5vc0XeOgtu8w7hB17cgJLEXVmbwj0xztf4KGpd6nAS2/ZWYK2mrLLBR30ll21apXmczh16pTess9xbTT1Ht30ld6yixYt0tSbm5urt+zLL7+sKVtcXKy3bCznyFJsurAUUWd28qXFesuOHTtW629YX1lLu0b4+vpqlQ0PD9dZlq4R91/11wjGGFu6dKnesoZeI+p99tlnesumpKRoym7durXB/vLycmZq9d+Zg59PY3Ezz7XoNfj5tFaL+3FnFRMvJyYmIj4+HtOnT0dQUBDWr18PmUyGLVuMu9yTpbD1cINdJ5/7G2jaFYNwHAfn3sHGrVMgQPspz4ITGO93UZtfhE4LZ0LQjPsJzU3i1bpPrtfjbESw7+KHbp++g6CVr5slBkKsBa2la1k4xiz7mWi5XA6ZTIbvvvsOI0eO1GyfOnUqysrK8NNPPzU4pq6uDnV1dZr3FRUV8Pb2xq1bt+Do6NigvCUO10ilUpSnn4O8pAzirp1g4+qsMw4armlYtraqChkz30DhrvvrIYuc7BHy1Udwi4ls1nCNvKQMx56ajNLzl8CJRABjYDyPrqteh1tsX9z85ieU7jmC2gvq+/N0Df/WMR4f8rcgAIfv12+CoLoWWa+t1DmkCzQcpjWkrE1kMJYL1EPAP/zwg9bfrK4hXQBIG/wCKjKzwJTq37sQHMQ2IrR5sjci9m3VO0xrtCHdFpSlId376BpheNnWHtKtqKiAl5cXysvLG/0eM6aKigo4OTlh0ORfYSNu2YOJCnkVDiT3bZW4H3cWn/DdunUL7du3x6+//oqoqCjN9tdeew1HjhzByZMnGxyzbNkyvPvuuw220x8c+avKrByUpp2GjYsj2sbFQCiVPPwgPXi5HIU/7EfJ8QzYuDii/XPPaE01wiuV2OccClan+4Jfy3iMVamnScnb/ws6DIzCrwOnoKyRJcd4CCBo4VqV7eZNRdhHiwEAVVVVWl/S+tTeKkL6qJdQnpml2ebcJwThuz6HbVvXFsVECNFWn4S1asL33HGIWpjwKeVVOPDvaPr+bQVW89CGId58800sWHB/tYL6Hj5C/sqhWwAcugUYrT6BWAyvCSPgNWFE4/tFIvhMH4vrm7YDqocnai59QsAJhYjcsxkHOvaHqrxKaz8HBgagfiCZae1rSsAC+M19AbiX8BlC4uWB6BO7UHbqd9RczYNdQEc4hXWnlV0IsRI848G3cDHclh5Pms7i7+Fzc3ODUChEUVGR1vaioiJ4eno2eoytrS0cHR21XoQ8KgKXL4RLH/VqEpopcwSc+vUX9cmTyN4O/U/9CLu/TEwsF9qiRuygeV9l64RjnZ4Gzwn0DOreIxQg9N9rIXZ1aXZbOI6DS2RPtH/uGTiHB1OyRwghZmLxPXxisRhhYWFITU3V3MPH8zxSU1ORkJBg3uAIaQaRgz2iDiXjzuETKE07DXEbZ7QbNxy8Qonq7KtQtXECenRtcJzM3xsx5/agJu8WyjPOQ+zWBrf3HcGlXYeQgShcc+qEEjtPBBZlQsWJIBSoYOPkAJd+YfCeNgbiNs4o2nMYyqoayLw90X7S3yDx8qDpHgghjaJ5+CyLxSd8ALBgwQJMnToV4eHhiIiIwNq1a1FdXY3p06ebOzRCmoXjOLgNjILbwCit7RJP94cmYDIfL8h8vAAArk+GI/DDhfibVomJYKoVjU643SY6rIWRE0IeF4zxYC1cKYPRkG6rsYqEb8KECbh9+zbeeecdFBYWIiQkBPv27YOHh3mmfiDkUUerqxBCyOPFKhI+AEhISKAhXPLYeHBKDWs8HyHk0UdDupbFahI+Qh4XdnZ2rXpfXWufjxBiGRjjWzwkS0O6rcfin9IlhBBCCCH6UQ8fIYQQQgzG8wDfwiHZFj7zQQxAPXyEWJja2lqMGDECI0aM0FrKzFrORwixDIznjfIirYN6+AixMCqVCnv27NH8bG3nI4QQYnyU8BFCCCHEYPSUrmWhhI8QQgghBqOndC0L3cNHCCGEEKtTUlKCyZMnw9HREc7Ozpg5cyaqqqr0HrNx40bExMTA0dERHMehrKysWfX+/vvvePLJJyGRSODt7Y1Vq1YZs2nNQgkfIYQQQgxWP6Tb0pepTJ48GVlZWdi/fz9SUlJw9OhRvPjii3qPqampwbBhw/DWW281u96KigoMGTIEvr6+yMjIwOrVq7Fs2TJs3LjRaG1rDhrSJYQQQojBjPGUrame0r1w4QL27duH3377DeHh4QCApKQkxMXFYc2aNfDy8mr0uPnz5wMADh8+3Ox6k5OTIZfLsWXLFojFYnTr1g1nzpxBYmLiQxNOU6KEDwBj6v9hVFRUmDkSQh7uwVUvKioqTP7kbGufjxBiuPrvr/rvs9agUrZ8BZ76Ov76/WtrawtbW9tm15uWlgZnZ2dNUgYAgwYNgkAgwMmTJzFq1CiT1ZuWlob+/ftDLBZrygwdOhQrV65EaWkpXFxcmt2ulqCED0BlZSUAwNvb28yREGIYXf9LtZbzEUIMU1lZCScnJ5OeQywWw9PTE+mp441Sn729fYPv36VLl2LZsmXNrrOwsBBt27bV2iYSidCmTRsUFhaatN7CwkL4+flplfHw8NDso4TPjLy8vHDjxg04ODiA47gW11dRUQFvb2/cuHEDjo6ORojw0WHNbQOofZaO2mfZrLl9pm4bYwyVlZWt8p8yiUSC3NxcyOVyo9THGGvw3aurd++NN97AypUr9dZ34cIFo8RlbSjhAyAQCNChQwej1+vo6Gh1F6161tw2gNpn6ah9ls2a22fKtpm6Z+9BEokEEomk1c5Xb+HChZg2bZreMv7+/vD09ERxcbHWdqVSiZKSEnh6ejb7/E2p19PTE0VFRVpl6t+35NwtRQkfIYQQQiyCu7s73N3dH1ouKioKZWVlyMjIQFhYGADg4MGD4HkekZGRzT5/U+qNiorC4sWLoVAoYGNjAwDYv38/unTpYrbhXICmZSGEEEKIlenatSuGDRuG+Ph4nDp1CsePH0dCQgImTpyoGfbOz89HYGAgTp06pTmusLAQZ86cweXLlwEA586dw5kzZ1BSUtLkeidNmgSxWIyZM2ciKysLO3bswCeffIIFCxa08qegjRI+E7C1tcXSpUtb9ITRo8qa2wZQ+ywdtc+yWXP7rLltj6rk5GQEBgYiNjYWcXFx6Nevn9ZceAqFAtnZ2aipqdFsW79+PUJDQxEfHw8A6N+/P0JDQ7F79+4m1+vk5IT//e9/yM3NRVhYGBYuXIh33nnHrFOyAADHWvMZbkIIIYQQ0uqoh48QQgghxMpRwkcIIYQQYuUo4SOEEEIIsXKU8BFCCCGEWDlK+FrBf/7zH0RGRkIqlcLFxQUjR440d0hGV1dXh5CQEHAchzNnzpg7HKO4du0aZs6cCT8/P0ilUnTq1AlLly412uzy5rBu3Tp07NgREokEkZGRWtMRWLIVK1agd+/ecHBwQNu2bTFy5EhkZ2ebOyyT+Mc//gGO4zSLvFuD/Px8TJkyBa6urpBKpQgODkZ6erq5wzIKlUqFt99+W+s68v7777fqmreEADTxssnt2rUL8fHxWL58OZ566ikolUqcP3/e3GEZ3WuvvQYvLy+cPXvW3KEYzcWLF8HzPDZs2IAnnngC58+fR3x8PKqrq7FmzRpzh2ewHTt2YMGCBVi/fj0iIyOxdu1aDB06FNnZ2Q3WhrQ0R44cwezZs9G7d28olUq89dZbGDJkCP744w/Y2dmZOzyj+e2337Bhwwb06NHD3KEYTWlpKaKjozFw4EDs3bsX7u7uyMnJMesEtca0cuVKfPHFF9i2bRu6deuG9PR0TJ8+HU5OTpg7d665wyOPE0ZMRqFQsPbt27PNmzebOxST2rNnDwsMDGRZWVkMADt9+rS5QzKZVatWMT8/P3OH0SwRERFs9uzZmvcqlYp5eXmxFStWmDEq0yguLmYA2JEjR8wditFUVlaygIAAtn//fjZgwAA2b948c4dkFK+//jrr16+fucMwmREjRrAZM2ZobRs9ejSbPHmymSIijysa0jWhzMxM5OfnQyAQIDQ0FO3atcPw4cOtqoevqKgI8fHx+PrrryGTycwdjsmVl5ejTZs25g7DYHK5HBkZGRg0aJBmm0AgwKBBg5CWlmbGyEyjvLwcACzyd6XL7NmzMWLECK3foTXYvXs3wsPDMW7cOLRt2xahoaHYtGmTucMymr59+yI1NRWXLl0CAJw9exbHjh3D8OHDzRwZedxQwmdCV69eBQAsW7YMS5YsQUpKClxcXBATE6NZpsWSMcYwbdo0zJo1C+Hh4eYOx+QuX76MpKQk/P3vfzd3KAb7888/oVKp4OHhobXdw8MDhYWFZorKNHiex/z58xEdHY3u3bubOxyj2L59OzIzM7FixQpzh2J0V69exRdffIGAgAD897//xUsvvYS5c+di27Zt5g7NKN544w1MnDgRgYGBsLGxQWhoKObPn4/JkyebOzTymKGErxneeOMNcByn91V//xcALF68GGPGjEFYWBi2bt0KjuPw7bffmrkVujW1fUlJSaisrMSbb75p7pAN0tT2PSg/Px/Dhg3DuHHjNEvukEfT7Nmzcf78eWzfvt3coRjFjRs3MG/ePCQnJ0MikZg7HKPjeR69evXC8uXLERoaihdffBHx8fFYv369uUMzip07dyI5ORnffPMNMjMzsW3bNqxZs8ZqElpiOeihjWZYuHAhpk2bpreMv78/CgoKAABBQUGa7ba2tvD390deXp4pQ2yRprbv4MGDSEtLa7A2ZHh4OCZPnvzIXtCa2r56t27dwsCBA9G3b1+t9RItiZubG4RCIYqKirS2FxUVwdPT00xRGV9CQgJSUlJw9OhRdOjQwdzhGEVGRgaKi4vRq1cvzTaVSoWjR4/is88+Q11dHYRCoRkjbJl27dppXSMB9QL1u3btMlNExvXqq69qevkAIDg4GNevX8eKFSswdepUM0dHHieU8DWDu7s73N3dH1ouLCwMtra2yM7ORr9+/QCoF2u+du0afH19TR1mszW1fZ9++ik++OADzftbt25h6NCh2LFjByIjI00ZYos0tX2Aumdv4MCBmt5ZgcAyO8XFYjHCwsKQmpqqmRaI53mkpqYiISHBvMEZAWMMc+bMwQ8//IDDhw/Dz8/P3CEZTWxsLM6dO6e1bfr06QgMDMTrr79u0ckeAERHRzeYQufSpUuP9DXSEDU1NQ2uG0KhUDMCREhroYTPhBwdHTFr1iwsXboU3t7e8PX1xerVqwEA48aNM3N0Lefj46P13t7eHgDQqVMnq+hdyc/PR0xMDHx9fbFmzRrcvn1bs88Se8UWLFiAqVOnIjw8HBEREVi7di2qq6sxffp0c4fWYrNnz8Y333yDn376CQ4ODpr7Ep2cnCCVSs0cXcs4ODg0uBfRzs4Orq6uVnGP4iuvvIK+ffti+fLlGD9+PE6dOoWNGzdabG/6Xz3zzDP48MMP4ePjg27duuH06dNITEzEjBkzzB0aedyY+zFhayeXy9nChQtZ27ZtmYODAxs0aBA7f/68ucMyidzcXKualmXr1q0MQKMvS5WUlMR8fHyYWCxmERER7MSJE+YOySh0/Z62bt1q7tBMwpqmZWGMsZ9//pl1796d2drassDAQLZx40Zzh2Q0FRUVbN68eczHx4dJJBLm7+/PFi9ezOrq6swdGnnMcIzRdN+EEEIIIdbMMm9IIoQQQgghTUYJHyGEEEKIlaOEjxBCCCHEylHCRwghhBBi5SjhI4QQQgixcpTwEUIIIYRYOUr4CCGEEEKsHCV8hBBCCCFWjhI+QoiWmJgYzJ8/39xhEEIIMSJK+AghJvXll1+C47gGr82bN2vKyOVyrFq1Cj179oRMJoObmxuio6OxdetWKBQKM0ZPCCHWQWTuAAgh1s/R0RHZ2dla25ycnACok72hQ4fi7NmzeP/99xEdHQ1HR0ecOHECa9asQWhoKEJCQswQNSGEWA/q4SOE6FRaWooXXngBLi4ukMlkGD58OHJycrTKbNq0Cd7e3pDJZBg1ahQSExPh7OysVYbjOHh6emq9pFIpAGDt2rU4evQoUlNTMXv2bISEhMDf3x+TJk3CyZMnERAQAAD47rvvEBwcDKlUCldXVwwaNAjV1dWt8jkQQoilo4SPEKLTtGnTkJ6ejt27dyMtLQ2MMcTFxWmGWY8fP45Zs2Zh3rx5OHPmDAYPHowPP/zQoHMkJydj0KBBCA0NbbDPxsYGdnZ2KCgowHPPPYcZM2bgwoULOHz4MEaPHg3GmFHaSQgh1o6GdAkhjcrJycHu3btx/Phx9O3bF4A6OfP29saPP/6IcePGISkpCcOHD8eiRYsAAJ07d8avv/6KlJQUrbrKy8thb2+veW9vb4/CwkLNeWJiYvTGUlBQAKVSidGjR8PX1xcAEBwcbKymEkKI1aOEjxDSqAsXLkAkEiEyMlKzzdXVFV26dMGFCxcAANnZ2Rg1apTWcREREQ0SPgcHB2RmZmreCwT3Bxea0kvXs2dPxMbGIjg4GEOHDsWQIUMwduxYuLi4NKtthBDyuKEhXUKIyQkEAjzxxBOal7+/v2Zf586dcfHiRb3HC4VC7N+/H3v37kVQUBCSkpLQpUsX5Obmmjp0QgixCpTwEUIa1bVrVyiVSpw8eVKz7c6dO8jOzkZQUBAAoEuXLvjtt9+0jvvr+4eZNGkSDhw4gNOnTzfYp1AoNA9mcByH6OhovPvuuzh9+jTEYjF++OEHQ5tFCCGPJUr4CCGNCggIwLPPPov4+HgcO3YMZ8+exZQpU9C+fXs8++yzAIA5c+Zgz549SExMRE5ODjZs2IC9e/eC47gmn2f+/PmIjo5GbGws1q1bh7Nnz+Lq1avYuXMn+vTpg5ycHJw8eRLLly9Heno68vLy8P333+P27dvo2rWrqZpPCCFWhRI+QohOW7duRVhYGJ5++mlERUWBMYY9e/bAxsYGABAdHY3169cjMTERPXv2xL59+/DKK69AIpE0+Ry2trbYv38/XnvtNWzYsAF9+vRB79698emnn2Lu3Lno3r07HB0dcfToUcTFxaFz585YsmQJPvroIwwfPtxUTSeEEKvCMZrXgBBiRPHx8bh48SJ++eUXc4dCCCHkHnpKlxDSImvWrMHgwYNhZ2eHvXv3Ytu2bfj888/NHRYhhJAHUA8fIaRFxo8fj8OHD6OyshL+/v6YM2cOZs2aZe6wCCGEPIASPkIIIYQQK0cPbRBCCCGEWDlK+AghhBBCrBwlfIQQQgghVo4SPkIIIYQQK0cJHyGEEEKIlaOEjxBCCCHEylHCRwghhBBi5SjhI4QQQgixcv8Pf/MKnYr8O1sAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 700x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Extract logFCs and pvals\n",
    "logFCs = results_df[['log2FoldChange']].T.rename(index={'log2FoldChange': 'treatment.vs.control'})\n",
    "pvals = results_df[['padj']].T.rename(index={'padj': 'treatment.vs.control'})\n",
    "\n",
    "# Plot\n",
    "dc.plot_volcano(\n",
    "    logFCs,\n",
    "    pvals,\n",
    "    'treatment.vs.control',\n",
    "    name='SRF',\n",
    "    net=collectri,\n",
    "    top=10,\n",
    "    sign_thr=0.05,\n",
    "    lFCs_thr=0.5\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9efaec0f-ac00-49a4-8297-53a310ec1bb3",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Pathway activity inference\n",
    "\n",
    "Another analysis we can perform is to infer pathway activities from our transcriptomics data.\n",
    "\n",
    "### PROGENy model\n",
    "\n",
    "[PROGENy](https://saezlab.github.io/progeny/) is a comprehensive resource containing a curated collection of pathways and their target genes, with weights for each interaction.\n",
    "For this example we will use the human weights (other organisms are available) and we will use the top 500 responsive genes ranked by p-value. Here is a brief description of each pathway:\n",
    "\n",
    "- **Androgen**: involved in the growth and development of the male reproductive organs.\n",
    "- **EGFR**: regulates growth, survival, migration, apoptosis, proliferation, and differentiation in mammalian cells\n",
    "- **Estrogen**: promotes the growth and development of the female reproductive organs.\n",
    "- **Hypoxia**: promotes angiogenesis and metabolic reprogramming when O2 levels are low.\n",
    "- **JAK-STAT**: involved in immunity, cell division, cell death, and tumor formation.\n",
    "- **MAPK**: integrates external signals and promotes cell growth and proliferation.\n",
    "- **NFkB**: regulates immune response, cytokine production and cell survival.\n",
    "- **p53**: regulates cell cycle, apoptosis, DNA repair and tumor suppression.\n",
    "- **PI3K**: promotes growth and proliferation.\n",
    "- **TGFb**: involved in development, homeostasis, and repair of most tissues.\n",
    "- **TNFa**: mediates haematopoiesis, immune surveillance, tumour regression and protection from infection.\n",
    "- **Trail**: induces apoptosis.\n",
    "- **VEGF**: mediates angiogenesis, vascular permeability, and cell migration.\n",
    "- **WNT**: regulates organ morphogenesis during development and tissue repair.\n",
    "\n",
    "To access it we can use `decoupler`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e646969e-c4f6-48a5-8d19-848746ac7140",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>source</th>\n",
       "      <th>target</th>\n",
       "      <th>weight</th>\n",
       "      <th>p_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Androgen</td>\n",
       "      <td>TMPRSS2</td>\n",
       "      <td>11.490631</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Androgen</td>\n",
       "      <td>NKX3-1</td>\n",
       "      <td>10.622551</td>\n",
       "      <td>2.242078e-44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Androgen</td>\n",
       "      <td>MBOAT2</td>\n",
       "      <td>10.472733</td>\n",
       "      <td>4.624285e-44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Androgen</td>\n",
       "      <td>KLK2</td>\n",
       "      <td>10.176186</td>\n",
       "      <td>1.944414e-40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Androgen</td>\n",
       "      <td>SARG</td>\n",
       "      <td>11.386852</td>\n",
       "      <td>2.790209e-40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6995</th>\n",
       "      <td>p53</td>\n",
       "      <td>ZMYM4</td>\n",
       "      <td>-2.325752</td>\n",
       "      <td>1.522388e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6996</th>\n",
       "      <td>p53</td>\n",
       "      <td>CFDP1</td>\n",
       "      <td>-1.628168</td>\n",
       "      <td>1.526045e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6997</th>\n",
       "      <td>p53</td>\n",
       "      <td>VPS37D</td>\n",
       "      <td>2.309503</td>\n",
       "      <td>1.537098e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6998</th>\n",
       "      <td>p53</td>\n",
       "      <td>TEDC1</td>\n",
       "      <td>-2.274823</td>\n",
       "      <td>1.547037e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6999</th>\n",
       "      <td>p53</td>\n",
       "      <td>CCDC138</td>\n",
       "      <td>-3.205113</td>\n",
       "      <td>1.568160e-06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7000 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        source   target     weight       p_value\n",
       "0     Androgen  TMPRSS2  11.490631  0.000000e+00\n",
       "1     Androgen   NKX3-1  10.622551  2.242078e-44\n",
       "2     Androgen   MBOAT2  10.472733  4.624285e-44\n",
       "3     Androgen     KLK2  10.176186  1.944414e-40\n",
       "4     Androgen     SARG  11.386852  2.790209e-40\n",
       "...        ...      ...        ...           ...\n",
       "6995       p53    ZMYM4  -2.325752  1.522388e-06\n",
       "6996       p53    CFDP1  -1.628168  1.526045e-06\n",
       "6997       p53   VPS37D   2.309503  1.537098e-06\n",
       "6998       p53    TEDC1  -2.274823  1.547037e-06\n",
       "6999       p53  CCDC138  -3.205113  1.568160e-06\n",
       "\n",
       "[7000 rows x 4 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Retrieve PROGENy model weights\n",
    "progeny = dc.get_progeny(top=500)\n",
    "progeny"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94b757a3-e7b9-4c2a-9081-4a3b4a17ee3e",
   "metadata": {},
   "source": [
    "### Activity inference with Multivariate Linear Model (MLM)\n",
    "\n",
    "To infer pathway enrichment scores we will run the Multivariate Linear Model (`mlm`) method. For each sample in our dataset (`adata`), it fits a linear model that predicts the observed gene expression based on all pathways' Pathway-Gene interactions weights.\n",
    "Once fitted, the obtained t-values of the slopes are the scores. If it is positive, we interpret that the pathway is active and if it is negative we interpret that it is inactive.\n",
    "\n",
    "<img src=\"../mlm.png\" />\n",
    "     \n",
    "We can run `mlm` with a one-liner:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "bd82e675-cb82-4fbe-8b93-50ceb73b7373",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running mlm on mat with 1 samples and 19713 targets for 14 sources.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Androgen</th>\n",
       "      <th>EGFR</th>\n",
       "      <th>Estrogen</th>\n",
       "      <th>Hypoxia</th>\n",
       "      <th>JAK-STAT</th>\n",
       "      <th>MAPK</th>\n",
       "      <th>NFkB</th>\n",
       "      <th>PI3K</th>\n",
       "      <th>TGFb</th>\n",
       "      <th>TNFa</th>\n",
       "      <th>Trail</th>\n",
       "      <th>VEGF</th>\n",
       "      <th>WNT</th>\n",
       "      <th>p53</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>treatment.vs.control</th>\n",
       "      <td>2.338243</td>\n",
       "      <td>-1.959179</td>\n",
       "      <td>1.244277</td>\n",
       "      <td>6.153507</td>\n",
       "      <td>-12.091851</td>\n",
       "      <td>8.071877</td>\n",
       "      <td>1.490978</td>\n",
       "      <td>7.937943</td>\n",
       "      <td>39.796871</td>\n",
       "      <td>-6.097804</td>\n",
       "      <td>-2.286829</td>\n",
       "      <td>3.763988</td>\n",
       "      <td>-0.376275</td>\n",
       "      <td>-6.113982</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Androgen      EGFR  Estrogen   Hypoxia   JAK-STAT  \\\n",
       "treatment.vs.control  2.338243 -1.959179  1.244277  6.153507 -12.091851   \n",
       "\n",
       "                          MAPK      NFkB      PI3K       TGFb      TNFa  \\\n",
       "treatment.vs.control  8.071877  1.490978  7.937943  39.796871 -6.097804   \n",
       "\n",
       "                         Trail      VEGF       WNT       p53  \n",
       "treatment.vs.control -2.286829  3.763988 -0.376275 -6.113982  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Infer pathway activities with mlm\n",
    "pathway_acts, pathway_pvals = dc.run_mlm(mat=mat, net=progeny, verbose=True)\n",
    "pathway_acts"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96d8aa60-3cff-476e-8050-a911932b1059",
   "metadata": {},
   "source": [
    "Let us plot the obtained scores:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ea55464a-8ead-408c-b9ce-0d8284758bcc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dc.plot_barplot(\n",
    "    pathway_acts,\n",
    "    'treatment.vs.control',\n",
    "    top=25,\n",
    "    vertical=False,\n",
    "    figsize=(6, 3)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90c413af-aaca-42a7-9980-c7bd8a6cd81d",
   "metadata": {},
   "source": [
    "As expected, after treating cells with the cytokine TGFb we see an increase of activity for this pathway.\n",
    "\n",
    "On the other hand, it seems that this treatment has decreased the activity of other pathways like JAK-STAT or TNFa.\n",
    "\n",
    "We can visualize the targets of TFGb in a scatter plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "6a237ad3-bae4-4fa2-b265-51b938f90250",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dc.plot_targets(results_df, stat='stat', source_name='TGFb', net=progeny, top=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49c87ac5",
   "metadata": {},
   "source": [
    "The observed activation of TGFb is due to the fact that majority of its target genes with positive weights have positive\n",
    "t-values (1st quadrant), and the majority of the ones with negative weights have negative t-values (3d quadrant)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2bf0d157",
   "metadata": {},
   "source": [
    "## Functional enrichment of biological terms\n",
    "\n",
    "Finally, we can also infer activities for general biological terms or processes.\n",
    "\n",
    "### MSigDB gene sets\n",
    "\n",
    "The Molecular Signatures Database ([MSigDB](http://www.gsea-msigdb.org/gsea/msigdb/)) is a resource containing a collection of gene sets annotated to different biological processes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e781e130-7674-40ad-bed9-80f44d8d100a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>genesymbol</th>\n",
       "      <th>collection</th>\n",
       "      <th>geneset</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MAFF</td>\n",
       "      <td>chemical_and_genetic_perturbations</td>\n",
       "      <td>BOYAULT_LIVER_CANCER_SUBCLASS_G56_DN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MAFF</td>\n",
       "      <td>chemical_and_genetic_perturbations</td>\n",
       "      <td>ELVIDGE_HYPOXIA_UP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MAFF</td>\n",
       "      <td>chemical_and_genetic_perturbations</td>\n",
       "      <td>NUYTTEN_NIPP1_TARGETS_DN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MAFF</td>\n",
       "      <td>immunesigdb</td>\n",
       "      <td>GSE17721_POLYIC_VS_GARDIQUIMOD_4H_BMDC_DN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MAFF</td>\n",
       "      <td>chemical_and_genetic_perturbations</td>\n",
       "      <td>SCHAEFFER_PROSTATE_DEVELOPMENT_12HR_UP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3838543</th>\n",
       "      <td>PRAMEF22</td>\n",
       "      <td>go_biological_process</td>\n",
       "      <td>GOBP_POSITIVE_REGULATION_OF_CELL_POPULATION_PR...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3838544</th>\n",
       "      <td>PRAMEF22</td>\n",
       "      <td>go_biological_process</td>\n",
       "      <td>GOBP_APOPTOTIC_PROCESS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3838545</th>\n",
       "      <td>PRAMEF22</td>\n",
       "      <td>go_biological_process</td>\n",
       "      <td>GOBP_REGULATION_OF_CELL_DEATH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3838546</th>\n",
       "      <td>PRAMEF22</td>\n",
       "      <td>go_biological_process</td>\n",
       "      <td>GOBP_NEGATIVE_REGULATION_OF_DEVELOPMENTAL_PROCESS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3838547</th>\n",
       "      <td>PRAMEF22</td>\n",
       "      <td>go_biological_process</td>\n",
       "      <td>GOBP_NEGATIVE_REGULATION_OF_CELL_DEATH</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3838548 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        genesymbol                          collection  \\\n",
       "0             MAFF  chemical_and_genetic_perturbations   \n",
       "1             MAFF  chemical_and_genetic_perturbations   \n",
       "2             MAFF  chemical_and_genetic_perturbations   \n",
       "3             MAFF                         immunesigdb   \n",
       "4             MAFF  chemical_and_genetic_perturbations   \n",
       "...            ...                                 ...   \n",
       "3838543   PRAMEF22               go_biological_process   \n",
       "3838544   PRAMEF22               go_biological_process   \n",
       "3838545   PRAMEF22               go_biological_process   \n",
       "3838546   PRAMEF22               go_biological_process   \n",
       "3838547   PRAMEF22               go_biological_process   \n",
       "\n",
       "                                                   geneset  \n",
       "0                     BOYAULT_LIVER_CANCER_SUBCLASS_G56_DN  \n",
       "1                                       ELVIDGE_HYPOXIA_UP  \n",
       "2                                 NUYTTEN_NIPP1_TARGETS_DN  \n",
       "3                GSE17721_POLYIC_VS_GARDIQUIMOD_4H_BMDC_DN  \n",
       "4                   SCHAEFFER_PROSTATE_DEVELOPMENT_12HR_UP  \n",
       "...                                                    ...  \n",
       "3838543  GOBP_POSITIVE_REGULATION_OF_CELL_POPULATION_PR...  \n",
       "3838544                             GOBP_APOPTOTIC_PROCESS  \n",
       "3838545                      GOBP_REGULATION_OF_CELL_DEATH  \n",
       "3838546  GOBP_NEGATIVE_REGULATION_OF_DEVELOPMENTAL_PROCESS  \n",
       "3838547             GOBP_NEGATIVE_REGULATION_OF_CELL_DEATH  \n",
       "\n",
       "[3838548 rows x 3 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "msigdb = dc.get_resource('MSigDB')\n",
    "msigdb"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f181de19-6079-4524-8342-476ac46c5a20",
   "metadata": {},
   "source": [
    "As an example, we will use the hallmark gene sets, but we could have used any other. \n",
    "\n",
    "<div class=\"alert alert-info\">\n",
    "\n",
    "**Note**\n",
    "    \n",
    "To see what other collections are available in MSigDB, type: `msigdb['collection'].unique()`.\n",
    "\n",
    "</div>  \n",
    "\n",
    "We can filter by for `hallmark`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "648addb3-349c-4df3-baea-322a363bd641",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>genesymbol</th>\n",
       "      <th>collection</th>\n",
       "      <th>geneset</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>MAFF</td>\n",
       "      <td>hallmark</td>\n",
       "      <td>IL2_STAT5_SIGNALING</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>MAFF</td>\n",
       "      <td>hallmark</td>\n",
       "      <td>COAGULATION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>270</th>\n",
       "      <td>MAFF</td>\n",
       "      <td>hallmark</td>\n",
       "      <td>HYPOXIA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>MAFF</td>\n",
       "      <td>hallmark</td>\n",
       "      <td>TNFA_SIGNALING_VIA_NFKB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>377</th>\n",
       "      <td>MAFF</td>\n",
       "      <td>hallmark</td>\n",
       "      <td>COMPLEMENT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1449668</th>\n",
       "      <td>STXBP1</td>\n",
       "      <td>hallmark</td>\n",
       "      <td>PANCREAS_BETA_CELLS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1450315</th>\n",
       "      <td>ELP4</td>\n",
       "      <td>hallmark</td>\n",
       "      <td>PANCREAS_BETA_CELLS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1450526</th>\n",
       "      <td>GCG</td>\n",
       "      <td>hallmark</td>\n",
       "      <td>PANCREAS_BETA_CELLS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1450731</th>\n",
       "      <td>PCSK2</td>\n",
       "      <td>hallmark</td>\n",
       "      <td>PANCREAS_BETA_CELLS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1450916</th>\n",
       "      <td>PAX6</td>\n",
       "      <td>hallmark</td>\n",
       "      <td>PANCREAS_BETA_CELLS</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7318 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        genesymbol collection                  geneset\n",
       "233           MAFF   hallmark      IL2_STAT5_SIGNALING\n",
       "250           MAFF   hallmark              COAGULATION\n",
       "270           MAFF   hallmark                  HYPOXIA\n",
       "373           MAFF   hallmark  TNFA_SIGNALING_VIA_NFKB\n",
       "377           MAFF   hallmark               COMPLEMENT\n",
       "...            ...        ...                      ...\n",
       "1449668     STXBP1   hallmark      PANCREAS_BETA_CELLS\n",
       "1450315       ELP4   hallmark      PANCREAS_BETA_CELLS\n",
       "1450526        GCG   hallmark      PANCREAS_BETA_CELLS\n",
       "1450731      PCSK2   hallmark      PANCREAS_BETA_CELLS\n",
       "1450916       PAX6   hallmark      PANCREAS_BETA_CELLS\n",
       "\n",
       "[7318 rows x 3 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filter by hallmark\n",
    "msigdb = msigdb[msigdb['collection']=='hallmark']\n",
    "\n",
    "# Remove duplicated entries\n",
    "msigdb = msigdb[~msigdb.duplicated(['geneset', 'genesymbol'])]\n",
    "\n",
    "# Rename\n",
    "msigdb.loc[:, 'geneset'] = [name.split('HALLMARK_')[1] for name in msigdb['geneset']]\n",
    "\n",
    "msigdb"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da91373b-d21a-4f17-9af3-bfcfb6318291",
   "metadata": {},
   "source": [
    "### Enrichment with Over Representation Analysis (ORA)\n",
    "\n",
    "To infer functional enrichment scores we will run the Over Representation Analysis (`ora`) method.\n",
    "As input data it accepts an expression matrix (`decoupler.run_ora`) or the results of differential expression analysis (`decoupler.run_ora_df`).\n",
    "For the former, by default the top 5% of expressed genes by sample are selected as the set of interest (S*), and for the latter a user-defined\n",
    "significance filtering can be used.\n",
    "Once we have S*, it builds a contingency table using set operations for each set stored in the gene set resource being used (`net`).\n",
    "Using the contingency table, `ora` performs a one-sided Fisher exact test to test for significance of overlap between sets.\n",
    "The final score is obtained by log-transforming the obtained p-values, meaning that higher values are more significant.\n",
    "\n",
    "<img src=\"../ora.png\" />\n",
    "     \n",
    "We can run `ora` with a simple one-liner:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "372e0583",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Term</th>\n",
       "      <th>Set size</th>\n",
       "      <th>Overlap ratio</th>\n",
       "      <th>p-value</th>\n",
       "      <th>FDR p-value</th>\n",
       "      <th>Odds ratio</th>\n",
       "      <th>Combined score</th>\n",
       "      <th>Features</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ADIPOGENESIS</td>\n",
       "      <td>200</td>\n",
       "      <td>0.625000</td>\n",
       "      <td>0.000209</td>\n",
       "      <td>0.000872</td>\n",
       "      <td>1.257682</td>\n",
       "      <td>10.655318</td>\n",
       "      <td>ABCA1;ACAA2;ACADM;ACADS;ACLY;ACOX1;ADCY6;ADIPO...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ALLOGRAFT_REJECTION</td>\n",
       "      <td>200</td>\n",
       "      <td>0.370000</td>\n",
       "      <td>0.999914</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.742748</td>\n",
       "      <td>0.000064</td>\n",
       "      <td>ABCE1;ABI1;APBB1;B2M;BCAT1;BCL10;BCL3;BRCA1;C2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ANDROGEN_RESPONSE</td>\n",
       "      <td>100</td>\n",
       "      <td>0.610000</td>\n",
       "      <td>0.016489</td>\n",
       "      <td>0.037476</td>\n",
       "      <td>1.227798</td>\n",
       "      <td>5.040152</td>\n",
       "      <td>ABCC4;ABHD2;ACTN1;ADAMTS1;ALDH1A3;ANKH;ARID5B;...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ANGIOGENESIS</td>\n",
       "      <td>36</td>\n",
       "      <td>0.527778</td>\n",
       "      <td>0.428919</td>\n",
       "      <td>0.536149</td>\n",
       "      <td>1.070826</td>\n",
       "      <td>0.906440</td>\n",
       "      <td>COL3A1;CXCL6;FGFR1;FSTL1;ITGAV;JAG1;LRPAP1;NRP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>APICAL_JUNCTION</td>\n",
       "      <td>200</td>\n",
       "      <td>0.555000</td>\n",
       "      <td>0.063878</td>\n",
       "      <td>0.106463</td>\n",
       "      <td>1.115798</td>\n",
       "      <td>3.069314</td>\n",
       "      <td>ACTA1;ACTB;ACTC1;ACTG1;ACTG2;ACTN1;ACTN4;ADAM1...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Term  Set size  Overlap ratio   p-value  FDR p-value  \\\n",
       "0         ADIPOGENESIS       200       0.625000  0.000209     0.000872   \n",
       "1  ALLOGRAFT_REJECTION       200       0.370000  0.999914     1.000000   \n",
       "2    ANDROGEN_RESPONSE       100       0.610000  0.016489     0.037476   \n",
       "3         ANGIOGENESIS        36       0.527778  0.428919     0.536149   \n",
       "4      APICAL_JUNCTION       200       0.555000  0.063878     0.106463   \n",
       "\n",
       "   Odds ratio  Combined score  \\\n",
       "0    1.257682       10.655318   \n",
       "1    0.742748        0.000064   \n",
       "2    1.227798        5.040152   \n",
       "3    1.070826        0.906440   \n",
       "4    1.115798        3.069314   \n",
       "\n",
       "                                            Features  \n",
       "0  ABCA1;ACAA2;ACADM;ACADS;ACLY;ACOX1;ADCY6;ADIPO...  \n",
       "1  ABCE1;ABI1;APBB1;B2M;BCAT1;BCL10;BCL3;BRCA1;C2...  \n",
       "2  ABCC4;ABHD2;ACTN1;ADAMTS1;ALDH1A3;ANKH;ARID5B;...  \n",
       "3  COL3A1;CXCL6;FGFR1;FSTL1;ITGAV;JAG1;LRPAP1;NRP...  \n",
       "4  ACTA1;ACTB;ACTC1;ACTG1;ACTG2;ACTN1;ACTN4;ADAM1...  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Infer enrichment with ora using significant deg\n",
    "top_genes = results_df[results_df['padj'] < 0.05]\n",
    "\n",
    "# Run ora\n",
    "enr_pvals = dc.get_ora_df(\n",
    "    df=top_genes,\n",
    "    net=msigdb,\n",
    "    source='geneset',\n",
    "    target='genesymbol'\n",
    ")\n",
    "\n",
    "enr_pvals.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c66b649",
   "metadata": {},
   "source": [
    "Then we can visualize the most enriched terms:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b7f8e504",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 300x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dc.plot_dotplot(\n",
    "    enr_pvals.sort_values('Combined score', ascending=False).head(15),\n",
    "    x='Combined score',\n",
    "    y='Term',\n",
    "    s='Odds ratio',\n",
    "    c='FDR p-value',\n",
    "    scale=1.5,\n",
    "    figsize=(3, 6)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c34d80d",
   "metadata": {},
   "source": [
    "TNFa and interferons response (JAK-STAT) processes seem to be enriched. We previously observed a similar result with the PROGENy pathways, were they were significantly downregulated. Therefore, one of the limitations of using a prior knowledge resource without weights is that it doesn't provide direction.\n",
    "\n",
    "We can also plot the running score for a given gene set:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "5b56414e-1120-445f-907f-a9a2da6428a6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot\n",
    "dc.plot_running_score(\n",
    "    df=results_df,\n",
    "    stat='stat',\n",
    "    net=msigdb,\n",
    "    source='geneset',\n",
    "    target='genesymbol',\n",
    "    set_name='TNFA_SIGNALING_VIA_NFKB'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66a1a653-5df2-4017-bc90-bd24bfd92e7f",
   "metadata": {},
   "source": [
    "## Enrichment of ligand-receptor interactions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97485bba-b413-4158-8941-a1cd19443295",
   "metadata": {},
   "source": [
    "Recently, study of interactions between ligands and receptors have gained significant traction, notably pushed by the democratization of single cell sequencing technologies. While most methods (such as the one described in LIANA) are developed for single cell datasets, they rely on a relatively simple assumption of co-expression or co-regulation of two (or more in the context of complexes) genes acting as ligand and receptors to propose hypothetical ligand-receptor interaction events. This concept can seamlessly be applied to a bulk RNA dataset, where the assumption is that sender and receiver cells are convoluted in a single dataset, but the observation of significant co-regulation of ligand and receptors should still correspond to hypothetical ligand-receptor interaction events.\n",
    "\n",
    "At the core, most current ligand-receptor interaction methods rely on averaging the measurements obtained for ligand and receptor and standardizing them against a background distribution.  Thus, an enrichment method based on a weighted mean can emulate this, where the sets are simply the members of a ligand receptor pair (or more in the context of complexes).\n",
    "\n",
    "Thus, we can extract ligand-receptor interaction ressources from the LIANA package (available both in [R](https://saezlab.github.io/liana/) and [python](https://liana-py.readthedocs.io/en/latest/)), and use it as a prior knowledge network with decoupler to find the most significant pairs of ligand-receptors in a given bulk dataset.\n",
    "\n",
    "While more work is required to fully understand the functional relevance of the highlighted ligand-receptor interactions with such an approach, this represents a very straightforward and intuitive approach to embed a bulk RNA dataset with ligand-receptor interaction prior knowledge.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7cadf02c-e62a-44e7-b03d-1174afbd4a98",
   "metadata": {},
   "source": [
    "First, we extract ligand-receptor interactions from liana, and decomplexify them to format them into an appropriate decoupleR input."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "8782c7fa-dc4e-445b-a57c-a51d24164155",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>interaction</th>\n",
       "      <th>genes</th>\n",
       "      <th>weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>LGALS9&amp;PTPRC</td>\n",
       "      <td>LGALS9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>LGALS9&amp;MET</td>\n",
       "      <td>LGALS9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>LGALS9&amp;CD44</td>\n",
       "      <td>LGALS9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LGALS9&amp;LRP1</td>\n",
       "      <td>LGALS9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LGALS9&amp;CD47</td>\n",
       "      <td>LGALS9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5775</th>\n",
       "      <td>BMP2&amp;ACTR2</td>\n",
       "      <td>ACTR2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5776</th>\n",
       "      <td>BMP15&amp;ACTR2</td>\n",
       "      <td>ACTR2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5777</th>\n",
       "      <td>CSF1&amp;CSF3R</td>\n",
       "      <td>CSF3R</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5778</th>\n",
       "      <td>IL36G&amp;IFNAR1</td>\n",
       "      <td>IFNAR1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5779</th>\n",
       "      <td>IL36G&amp;IFNAR2</td>\n",
       "      <td>IFNAR2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10381 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       interaction   genes  weight\n",
       "0     LGALS9&PTPRC  LGALS9       1\n",
       "1       LGALS9&MET  LGALS9       1\n",
       "2      LGALS9&CD44  LGALS9       1\n",
       "3      LGALS9&LRP1  LGALS9       1\n",
       "4      LGALS9&CD47  LGALS9       1\n",
       "...            ...     ...     ...\n",
       "5775    BMP2&ACTR2   ACTR2       1\n",
       "5776   BMP15&ACTR2   ACTR2       1\n",
       "5777    CSF1&CSF3R   CSF3R       1\n",
       "5778  IL36G&IFNAR1  IFNAR1       1\n",
       "5779  IL36G&IFNAR2  IFNAR2       1\n",
       "\n",
       "[10381 rows x 3 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import liana as ln\n",
    "\n",
    "liana_lr = ln.resource.select_resource()\n",
    "liana_lr = ln.resource.explode_complexes(liana_lr)\n",
    "\n",
    "# Create two new DataFrames, each containing one of the pairs of columns to be concatenated\n",
    "df1 = liana_lr[['interaction', 'ligand']]\n",
    "df2 = liana_lr[['interaction', 'receptor']]\n",
    "\n",
    "# Rename the columns in each new DataFrame\n",
    "df1.columns = ['interaction', 'genes']\n",
    "df2.columns = ['interaction', 'genes']\n",
    "\n",
    "# Concatenate the two new DataFrames\n",
    "liana_lr = pd.concat([df1, df2], axis=0)\n",
    "liana_lr['weight'] = 1\n",
    "\n",
    "# Find duplicated rows\n",
    "duplicates = liana_lr.duplicated()\n",
    "\n",
    "# Remove duplicated rows\n",
    "liana_lr = liana_lr[~duplicates]\n",
    "\n",
    "liana_lr"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9d440fc-04d8-44c8-b29c-5bb3fa8f3900",
   "metadata": {},
   "source": [
    "Then we can use `ulm` to find the significant co-regulated pairs of ligand and receptors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "0fd5af26-a8a7-42c3-a472-3228be499faf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running ulm on mat with 1 samples and 19713 targets for 2112 sources.\n"
     ]
    }
   ],
   "source": [
    "# Infer lr activities with ulm\n",
    "lr_score, lr_pvalue = dc.run_ulm(\n",
    "    mat=mat,\n",
    "    net=liana_lr,\n",
    "    source='interaction',\n",
    "    target='genes',\n",
    "    min_n=2,\n",
    "    verbose=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "d661b84d-d87c-492d-8f0f-aadc66a445e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dc.plot_barplot(lr_score, 'treatment.vs.control', top=25, vertical=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb7c3f3f-555d-47d0-a55c-de23dc54a3f2",
   "metadata": {},
   "source": [
    "Interactions between colagens and the ITG_ITG complexes seems to be quite enrichned. That is especially relevant since the EMT pathway was significantly enriched in the functional pathway analysis."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:decoupler]",
   "language": "python",
   "name": "conda-env-decoupler-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}