_analysis_VEX1_RNAi_2-soup_only_vsg.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "33195b2a",
   "metadata": {},
   "source": [
    "# Set up notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "49bd99c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext rpy2.ipython"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6da7731c",
   "metadata": {},
   "source": [
    "## r libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "444ebfbc",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%R\n",
    "library(dplyr)\n",
    "library(Seurat)\n",
    "library(patchwork)\n",
    "library(data.table)\n",
    "library(DropletUtils)\n",
    "library(scRNAseq)\n",
    "library(scater)\n",
    "library(scran)\n",
    "library(PCAtools)\n",
    "library(SoupX)\n",
    "library(celda)\n",
    "#library(EmptyDrops)\n",
    "set.seed(110010101)\n",
    "\n",
    "path_to <- \"VEX1_RNAi_2_count6/outs/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "dbb53931-6255-4291-a571-8168a4845ad6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R version 4.1.0 (2021-05-18)\n",
      "Platform: x86_64-conda-linux-gnu (64-bit)\n",
      "Running under: Red Hat Enterprise Linux\n",
      "\n",
      "Matrix products: default\n",
      "BLAS/LAPACK: /cluster/home/mtinti/miniconda3/envs/seurat2/lib/libopenblasp-r0.3.18.so\n",
      "\n",
      "locale:\n",
      " [1] LC_CTYPE=en_GB.UTF-8       LC_NUMERIC=C              \n",
      " [3] LC_TIME=en_GB.UTF-8        LC_COLLATE=en_GB.UTF-8    \n",
      " [5] LC_MONETARY=en_GB.UTF-8    LC_MESSAGES=en_GB.UTF-8   \n",
      " [7] LC_PAPER=en_GB.UTF-8       LC_NAME=C                 \n",
      " [9] LC_ADDRESS=C               LC_TELEPHONE=C            \n",
      "[11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C       \n",
      "\n",
      "attached base packages:\n",
      "[1] stats4    tools     stats     graphics  grDevices utils     datasets \n",
      "[8] methods   base     \n",
      "\n",
      "other attached packages:\n",
      " [1] celda_1.10.0                SoupX_1.5.2                \n",
      " [3] PCAtools_2.6.0              ggrepel_0.9.1              \n",
      " [5] scran_1.22.1                scater_1.22.0              \n",
      " [7] ggplot2_3.3.5               scuttle_1.4.0              \n",
      " [9] scRNAseq_2.8.0              DropletUtils_1.14.1        \n",
      "[11] SingleCellExperiment_1.16.0 SummarizedExperiment_1.24.0\n",
      "[13] Biobase_2.54.0              GenomicRanges_1.46.1       \n",
      "[15] GenomeInfoDb_1.30.0         IRanges_2.28.0             \n",
      "[17] S4Vectors_0.32.2            BiocGenerics_0.40.0        \n",
      "[19] MatrixGenerics_1.6.0        matrixStats_0.61.0         \n",
      "[21] data.table_1.14.2           patchwork_1.1.1            \n",
      "[23] SeuratObject_4.0.3          Seurat_4.0.5               \n",
      "[25] dplyr_1.0.7                \n",
      "\n",
      "loaded via a namespace (and not attached):\n",
      "  [1] rappdirs_0.3.3                MCMCprecision_0.4.0          \n",
      "  [3] rtracklayer_1.54.0            scattermore_0.7              \n",
      "  [5] R.methodsS3_1.8.1             tidyr_1.1.4                  \n",
      "  [7] bit64_4.0.5                   irlba_2.3.3                  \n",
      "  [9] DelayedArray_0.20.0           R.utils_2.11.0               \n",
      " [11] rpart_4.1-15                  KEGGREST_1.34.0              \n",
      " [13] RCurl_1.98-1.5                AnnotationFilter_1.18.0      \n",
      " [15] doParallel_1.0.16             generics_0.1.1               \n",
      " [17] GenomicFeatures_1.46.1        ScaledMatrix_1.2.0           \n",
      " [19] cowplot_1.1.1                 RSQLite_2.2.8                \n",
      " [21] RANN_2.6.1                    combinat_0.0-8               \n",
      " [23] future_1.23.0                 bit_4.0.4                    \n",
      " [25] spatstat.data_2.1-0           xml2_1.3.2                   \n",
      " [27] httpuv_1.6.3                  assertthat_0.2.1             \n",
      " [29] viridis_0.6.2                 hms_1.1.1                    \n",
      " [31] promises_1.2.0.1              fansi_0.4.2                  \n",
      " [33] restfulr_0.0.13               progress_1.2.2               \n",
      " [35] dbplyr_2.1.1                  assertive.files_0.0-2        \n",
      " [37] igraph_1.2.8                  DBI_1.1.1                    \n",
      " [39] htmlwidgets_1.5.4             spatstat.geom_2.3-0          \n",
      " [41] purrr_0.3.4                   ellipsis_0.3.2               \n",
      " [43] biomaRt_2.50.0                deldir_1.0-6                 \n",
      " [45] sparseMatrixStats_1.6.0       vctrs_0.3.8                  \n",
      " [47] ensembldb_2.18.2              ROCR_1.0-11                  \n",
      " [49] abind_1.4-5                   cachem_1.0.6                 \n",
      " [51] RcppEigen_0.3.3.9.1           withr_2.4.2                  \n",
      " [53] sctransform_0.3.2             GenomicAlignments_1.30.0     \n",
      " [55] prettyunits_1.1.1             goftest_1.2-3                \n",
      " [57] cluster_2.1.2                 ExperimentHub_2.2.0          \n",
      " [59] lazyeval_0.2.2                crayon_1.4.2                 \n",
      " [61] edgeR_3.36.0                  pkgconfig_2.0.3              \n",
      " [63] nlme_3.1-153                  vipor_0.4.5                  \n",
      " [65] ProtGenerics_1.26.0           rlang_0.4.12                 \n",
      " [67] globals_0.14.0                lifecycle_1.0.1              \n",
      " [69] miniUI_0.1.1.1                filelock_1.0.2               \n",
      " [71] BiocFileCache_2.2.0           enrichR_3.0                  \n",
      " [73] rsvd_1.0.5                    AnnotationHub_3.2.0          \n",
      " [75] polyclip_1.10-0               lmtest_0.9-39                \n",
      " [77] Matrix_1.3-4                  Rhdf5lib_1.16.0              \n",
      " [79] zoo_1.8-9                     beeswarm_0.4.0               \n",
      " [81] ggridges_0.5.3                png_0.1-7                    \n",
      " [83] viridisLite_0.4.0             rjson_0.2.20                 \n",
      " [85] bitops_1.0-7                  R.oo_1.24.0                  \n",
      " [87] KernSmooth_2.23-20            rhdf5filters_1.6.0           \n",
      " [89] Biostrings_2.62.0             blob_1.2.2                   \n",
      " [91] DelayedMatrixStats_1.16.0     stringr_1.4.0                \n",
      " [93] parallelly_1.29.0             gridGraphics_0.5-1           \n",
      " [95] beachmat_2.10.0               scales_1.1.1                 \n",
      " [97] memoise_2.0.0                 magrittr_2.0.1               \n",
      " [99] plyr_1.8.6                    ica_1.0-2                    \n",
      "[101] zlibbioc_1.40.0               compiler_4.1.0               \n",
      "[103] dqrng_0.3.0                   BiocIO_1.4.0                 \n",
      "[105] RColorBrewer_1.1-2            fitdistrplus_1.1-6           \n",
      "[107] Rsamtools_2.10.0              XVector_0.34.0               \n",
      "[109] listenv_0.8.0                 pbapply_1.5-0                \n",
      "[111] MASS_7.3-54                   mgcv_1.8-38                  \n",
      "[113] tidyselect_1.1.1              stringi_1.7.5                \n",
      "[115] yaml_2.2.1                    BiocSingular_1.10.0          \n",
      "[117] assertive.numbers_0.0-2       locfit_1.5-9.4               \n",
      "[119] grid_4.1.0                    future.apply_1.8.1           \n",
      "[121] parallel_4.1.0                bluster_1.4.0                \n",
      "[123] foreach_1.5.1                 metapod_1.2.0                \n",
      "[125] gridExtra_2.3                 assertive.types_0.0-3        \n",
      "[127] Rtsne_0.15                    digest_0.6.28                \n",
      "[129] BiocManager_1.30.16           shiny_1.7.1                  \n",
      "[131] Rcpp_1.0.7                    BiocVersion_3.14.0           \n",
      "[133] later_1.3.0                   RcppAnnoy_0.0.19             \n",
      "[135] httr_1.4.2                    AnnotationDbi_1.56.2         \n",
      "[137] assertive.properties_0.0-4    colorspace_2.0-2             \n",
      "[139] XML_3.99-0.8                  tensor_1.5                   \n",
      "[141] reticulate_1.22               splines_4.1.0                \n",
      "[143] uwot_0.1.10                   statmod_1.4.36               \n",
      "[145] spatstat.utils_2.2-0          plotly_4.10.0                \n",
      "[147] xtable_1.8-4                  jsonlite_1.7.2               \n",
      "[149] assertive.base_0.0-9          R6_2.5.1                     \n",
      "[151] pillar_1.6.4                  htmltools_0.5.2              \n",
      "[153] mime_0.12                     glue_1.5.0                   \n",
      "[155] fastmap_1.1.0                 BiocParallel_1.28.1          \n",
      "[157] BiocNeighbors_1.12.0          interactiveDisplayBase_1.32.0\n",
      "[159] codetools_0.2-18              utf8_1.2.2                   \n",
      "[161] lattice_0.20-45               spatstat.sparse_2.0-0        \n",
      "[163] tibble_3.1.6                  multipanelfigure_2.1.2       \n",
      "[165] curl_4.3.2                    ggbeeswarm_0.6.0             \n",
      "[167] leiden_0.3.9                  magick_2.7.3                 \n",
      "[169] survival_3.2-13               limma_3.50.0                 \n",
      "[171] munsell_0.5.0                 rhdf5_2.38.0                 \n",
      "[173] GenomeInfoDbData_1.2.7        iterators_1.0.13             \n",
      "[175] HDF5Array_1.22.1              reshape2_1.4.4               \n",
      "[177] gtable_0.3.0                  spatstat.core_2.3-1          \n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "sessionInfo()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "075e20c2",
   "metadata": {},
   "source": [
    "## python libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3e85a885-51ab-4e58-9783-e833d3bbc8c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "#!conda env export > environment.yml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3fc9e242",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy\n",
    "import seaborn as sns\n",
    "\n",
    "path_to = \"VEX1_RNAi_2_count6/outs/\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f4ae325",
   "metadata": {},
   "source": [
    "## Estimate and remove Background"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "079e415e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "R[write to console]: Loading raw count data\n",
      "\n",
      "R[write to console]: Loading cell-only count data\n",
      "\n",
      "R[write to console]: Loading extra analysis data where available\n",
      "\n",
      "R[write to console]: 5 genes passed tf-idf cut-off and 4 soup quantile filter.  Taking the top 4.\n",
      "\n",
      "R[write to console]: Using 10 independent estimates of rho.\n",
      "\n",
      "R[write to console]: Estimated global rho of 0.32\n",
      "\n",
      "R[write to console]: Estimated contamination is very high (0.32).\n",
      "\n",
      "R[write to console]: Expanding counts from 8 clusters to 6762 cells.\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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gYMiQIdRwBQ0NDf6Qhr179165coXH4xUVFW3bti0xMTE3N/fUqVMqKipHjhyhLj5+/PiBAwcWFBRQAyq4XG4Tx3k83q+//vrVV18J33QTl+LxeNQYjJKSkrpv5/79++np6enp6SEhIUZGRvyvBgYGTpo0ScS3XF1dra+vv2HDhqqqqvT09L59+86ZM4fH45WVlX38nxUrVgwcODAjI4O6ZmVlpY6OTnJycqM/Im0DAQ3Ccnd3/+/JpwE9fvz49PR0+kuijYGBQWhoqI2NjY6OzsyZMysqKqjjb9++HTRokKamZqdOnY4ePcrj8R48eODs7Kyurq6rq+vr65uXl8fj8U6fPm1qaqqlpVVvOBdPuIAW2FA9RUVF48aNU1FRMTIy2rVrF//4sGHDVqxYwePxSkpKPD09dXR0lJSUOnfuvH37duqEhv2qW7dubeI4j8fLz883MjIqLi4WsukmLsXj8QICAqZNm1bv7fzwww9aWlpKSkoeHh6vX7/mHx8+fDh/JEar3zL1berTp4+6urqent6kSZPy8/PrFVBvFMfp06d9fHwa/rO3NaxmB0IpKCiYNm3a2bNn/33+v9XsqGfLli3z8fHp06cPY/W1MSlfza4hIde3E6+amhoHB4dnz57V/UyVHkytqEdHH/SjR4/09fUtLCwqKirWrVt35coVQoi3t/d3331H/z80tE5ycrK5uXljX+3QoUNSUpIEBzTUI+T6duIlJyf35s0b+tslzK2oR8c46EmTJlEfIi1evPjcuXOBgYGzZs06c+YMzf/9gihSU1NNTU0b+2qHDh3oH4EEIPHouIP+8OED9bt9+vTpmJgYamcELy8vV1fXrVu3Nvaq7Ozs5OTkegcrKiosLS3rfYQNNEhNTW1iSwsLC4uTJ0/SWQ/NMjIymC4BpBEdAW1hYRETEzNixAgZGRkFBQXqoIKCQnl5eROvev36NdUZUldcXJyDg8OaNWvaqlZoREpKyrBhwxr7qrm5eUpKCp31AEgDOgJ6+fLlM2fOXL9+fVBQkK+v7+LFiwkhv/zyy7hx45p4lbu7u7u7e72DEREROTk5bVgrNCI9Pb3efIq6lJSUmv7vVsLgM0OgBx0BPW3aNB0dndWrVz979ozH4925c0dXV9ff3z8kJISG1kEs0tLSmu1Z4vF4zc65AADh0TST8Isvvvjiiy8qKyvT0tKUlZWbuBcDdiovL1dSUmriBH19/ezsbH19fdpKYgR/Oh8ADWhdzU5RUdHKygrpLJEkuxva0NBw48aN3bp14y/Ddu/evc6dO2tqak6bNo3L5VIHExIShgwZoq2t3blzZ4HLzBsaGoaFhXXs2FFNTW3RokUpKSnu7u5qamo+Pj6lpaXUOStXrrSwsFBXV3dxcYmKiiKE/PPPPzo6Ok+fPiWEpKen6+rqRkZG0vCugXG4F4DmVVRUNH37TAgxMzNLSUmhZ1mMT1RUkPR0ka6grEyEuGmgFgXlf8pNLQoqKyvbv3//iIgIPz8/alFQX1/fS5cuPXz4cPjw4ba2tnXXnKP88ccf9+7dKyoqcnV1vX//fnh4uJWV1bBhw/bt2xccHEwI6dy5c0xMjK6u7v79+8eNG5eUlGRtbb1x48ZJkyY9efJk+vTp06ZNGzBggEhvGdoJBDQ07+PHj83+3WNqasrMHfSLF2TfPpGuoKtL1q5t9izRFwXlv1BXV1dXV9fNzc3R0ZHaJX3MmDH8JZ4nTpxIPZg5c+batWvfvXvn5OQ0c+bMCxcu9OzZU0ZGpu7uUyDZENDQPGEC2szM7OHDh/TU84nu3Un37jS0I/qioBQq1gkhKioqdR9TCxwTQg4dOrRjx46MjAw5Obn09HT+sKWZM2d+8cUXe/bswfxb6YEdVaB5QgY0lVOSSvhFQamnDRcFFUZ8fHxwcPD+/ftTUlKSkpJMTU2p1XJKSkrmz58fEBCwevVqBhd3BZohoKF5wgS0gYFBZmYmPfWwU7du3QwMDNauXVtdXX337l2qY7qlFykqKlJRUbG1tSWEXLhwgT+BPjg42NXVdd++fSNGjJg1a5aYSwe2QkBD8zIzM/n7iTRGVla2pqaGnnrYSU5O7ty5c9HR0Xp6egEBAbt376YW+G8RV1fXiRMnuri4eHl53bt3j5oLc+7cuatXr4aHhxNCtmzZ8vTp0yNHjoj/DQD7tLPlRqmZhHPmzGG6EOkyc+bMJUuWULd1//p0uVHKoEGDbty40fTuIQAgPPwuQfMyMjKavYMm/5urQkM9AFICAQ3NKyoqorbmbJqpqalkf04IQDMENIiNiYlJWloa01UASA4ENDRPyCWQENAA4oWAhmYUFhYK079BCDE2Nk4XcdY1ANSBgIZmZGVlCblGHe6gAcQLAQ3NED6gcQcNIF4IaGiGMLNUKIqKipWVlW1dD4D0QEBDM3JycvT09IQ8uX3NewJgOQQ0NCMzM1P4fVKUlZX5C88DgIgQ0NCMFt1BGxsbf/z4sU3rAZAeCGhoRovuoPE5IYAYIaChGbm5uZ999pmQJyOgAcQIAQ3NqK6u5m/E1ywjIyMENIC4IKChGS0amIE7aAAxQkBDU3g8npALcVBMTEwQ0ADigoCGphQUFGhpaQl/Pja+AhAjBDQ0JTs7W/ghHIQQDofD3zUVAESEgIamZGdn6+rqtuglmEwIIC4IaGhKbm5uSwNaU1OzqKiojeoBkCoIaGhKVlZWSwPayMgIkwkBxAIBDU1pxR00RtoBiAsCGprSioDGXBUAcUFAQ1NycnKEn+dNwXpJAOKCgIam5OTk4A4agCkIaGhKUVGRkDvG8uEOGkBcENDQjBZN9SaYTAggPghoaEorZp3IycnV1NS0RTEA0gYBDY2qqamRl5dvxQsxmRBALBDQ0Ki8vLwWrZTEp6WlVVhYKPZ6AKQNAhoa1aK9VOrCQA4AsUBAQ6NaMUuFgoEcAGKBgIZGtWKWCgV30ABigYCGRuXl5bUuoHEHDSAWCGhoVKv7oLFeEoBYcGhu78WLF3/88UdNTY23t3ePHj1obh1apBXzvCkIaACxoOMOWktLq7KykhBy69at7t27x8TEvHjxws3N7fz58zS0Dq3W6jtofX39rKwssdcDIG3ouIMuLCykZi6sWbPmxx9/XLp0KSFk3759ISEhX3zxRWOvunr16pkzZ+odTExMdHFxadNqgS8vL09HR6cVL5SVla2trRV7PQDShtYujnfv3oWFhVGPR44cOX/+/CZOdnNz69ixY72Dly5dwiw12uTn57duogqFx+O1dB0PAKiLpoD+/fff5eXlZWRkKioqqCPl5eUcTlOtq6qqWllZ1TtoYGCQk5PTVlXCp2pra+Xk5Fr3Wh0dnfz8/NbdgAMAhY6AHjFixLlz5wghjo6O6enpTk5OhJDIyEjqAUgk6nNCBDSAKOgI6IsXLzY8OHr06FGjRtHQOjDCxMTk48ePDg4OTBcC0I7RPcyOT1VVlammQRjFxcXq6uqtfrmxsXFaWpoY6wGQQpioAoLl5eVpa2u3+uUmJiYYCg0gIgQ0CNbqed4UExMT3EEDiAgBDYK1eqUkCgIaQHQIaBBMxDtoTU3NoqIiMdYDIIUQ0CBYbm6uiIPkMKUIQEQIaBBM9GkmHA6Hy+WKqx4AKYSABsFavVISn6GhYUZGhrjqAZBCCGgQTPSANjExSU1NFVc9AFIIAQ2C5efnizIOmhBiamqKgRwAokBAg2BFRUWizCQkuIMGEBkCGhol4mKhpqamCGgAUSCgoa2giwNARAhoEEAsa+0bGBhkZmaKpR4A6YSABgEKCws1NTVFvAg2vgIQEQIaBGj1boQNIaMBWg0BDQKIuNYon4GBAbb3Bmg1BDQIIPosFYqZmVlKSoro1wGQTghoEEBcXRwIaABRIKBBAHFtyI2ABhAFAhoEEHG1fj5zc3MENECrIaBBgIKCArF8SGhmZpacnCz6dQCkEwIaBBB9tX6Knp5edna26NcBkE4IaBAgNzdXV1dX9OvIyMhgXxWAVkNAgwDFxcVqampiuZSCgkJVVZVYLgUgbRDQIIDoC3HwYSAHQKshoKFtWVhYfPjwgekqANolAQEdHBz85MkT+ksBlhDLUnZ85ubmGMgB0DoCAprH43l5eXXp0mX9+vX41ZJCou+lUpelpWVSUpK4rgYgVQQE9Pbt29PT0zdt2vT8+fMuXboMGjTowIEDRUVF9BcHjBDXEA4KujgAWk1wHzSHw/H29j5+/PiDBw9ycnL8/f0NDQ39/f3xaY80EONao4QQMzMzbHwF0DqCA7qgoGDv3r3u7u5ubm49e/a8fft2XFychoaGp6cnzfUB/UTfz7suDodTXV0trqsBSBVOw0Njxoy5evVq//79Z8+ePXLkSCUlJer4li1bNDQ06C0PGCDeO2hCCIfD4XK5HI6AHzYAaIKA35levXrt3LnTyMio3nFZWVlsMScNcnJy9PT0xHhBantvS0tLMV4TQBoI6OIwMDCol8579+6lHqiqqtJRFDBKXGuN8nXo0OH9+/divCCAlBAQ0CtXrqx3ZMmSJbQUA6wgru1U+BDQAK3zSRfH48ePCSFVVVXUA0pCQoIYR8UC+4lrQ0I+Kyurq1evivGCAFLik4AeOXIkISQrK4t6QAiRlZXV19cPDQ1loDRgSF5entjvoBMTE8V4QQAp8UlAU+NV58yZExYWxlA9wLzi4mLx/s1kbGyckZEhxgsCSIn/Avrx48cWFhZ6enr+/v51uzgon3/+Ob2FgeSQkZGpqalhugqA9ue/gPb19Q0JCZkyZYqvr2/D87CcAohCXV29qKgI4+gBWuS/gOZHMLJYmvF4PFlZ8S9Ca2Njk5iY6OzsLPYrA0gwAb+KMTExaWlphJDs7Ozg4ODFixcXFBSIt1VLS0vMeWGnwsLCtrjPtbGxSUhIEPtlASSbgJmEkydPvnnzJiFk/vz5xcXFqqqqgYGBJ06caHUbDVfw+Pjx48SJExUUFDD6im3EPgiaYm1t/fz5c7FfFkCyCQjorKwsMzOzqqqqixcv/vPPPxoaGmZmZqK0ER0d7erqOmLECP6Ru3fv9unTp+ld77hcbnFxcb2DpaWlolQCzRL7IGiKra3tqVOnxH5ZAMkmIKCVlJSys7OfP3/eqVMnXV1dLpdbWVkpShuvX7+eN2/evXv3tm3b1qFDB0JIaGjo3LlzDQ0Nm3jV+fPnd+3aVe9gZmbm0KFDRSkGmtZGd9CWlpZYFRqgpQQE9IwZM7p3715WVrZhwwZCSExMjI2NjShtWFpaXrhw4ezZs56enn5+fkuXLhXmVaNHjx49enS9gxERETk5OaIUA00T+ywVChYdBWgFAR8Srlmz5vTp09evX/f39yeEaGpqimXeysiRI58+fVpWVubs7Nyw7wJYoo26OAghampq+L4DtIjgJXpdXV35j+3t7cXVmKqq6saNG6dOnRodHa2pqSmuy4IY5eTkiPE7XpetrW18fHy3bt3a4uIAEklAQHO53BMnTvz9998lJSX8g+Hh4eJqskuXLl26dBHX1UC8xL7WKF+nTp3evXuHgAYQnoCAnj59+rt37zw8PLS0tOgvCJiVk5Mjxh1j67K1tb13715bXBlAUgkI6Pv3779580ZeXp7+aoBxubm5bXcH/dtvv7XFlQEklYAPCT/77DMZGRn6SwE2qKioUFZWbosrm5qaYld4gBYRcAc9evToiRMnzp07t+5wKwcHBxqrAgkkIyPD4/F4PB7++wcQkoCA3rp1KyHk9u3bdQ9iPV8QnZmZWWpqqogTUwGkh4CARhZLLS6Xy+EIHnkpFnZ2dnFxcQhoACEJXljy0qVL06ZNoybyxcTEXLt2jd6qgBn5+fltOnSnc+fOb968abvrA0gYAQG9devWhQsXurq6Pnv2jBCiqqracJ9vkEhttBAHHwIaoEUEBHRoaOj169fnzZunoKBACLGzs3v79i3thQED2jqgqcmEbXd9AAkjIKDLysr09fXrPm2jcVfANk98pSQAACAASURBVG0d0AoKCiKujAggVQQEtLu7+6pVq6hdPnk83urVqz08PGgvDBiQk5Ojp6fXpk3o6ellZ2e3aRMAEkNAQO/YsSM6OlpHRycpKcnIyOjBgwe//PIL/ZUB/fLy8tpoGiGfvb39q1ev2rQJAIkhYEyVkZHRvXv3YmNjP3z4YG5u7uTkhJkFUqLtFuLgowJ6wIABbdoKgGQQENCPHj26ffs2taqZsbEx0ll60HAH7eDgIJblxQGkwScBzeVyx48ff/bsWSsrK2Nj4/T09MWLF48bN+7w4cNycnJMlQi0yc7Obus+6I4dO2IgB4CQPumD3rFjx99///3kyZP4+PioqKj4+PhHjx7dv3+/4d6AIJEKCwvbeiMFBQWFioqKNm0CQGJ8EtDHjh3btGmTs7Mz/0i3bt02bdp0+PBh2gsDBtTW1srKCp5cKkbUH2dt3QqABPjktzEuLq537971zujduzdmf4EYOTg4vHz5kukqANqBTwK6uLjYwMCg3hlGRkbY61Ma0LYQKAIaQEj1R3EcPXq03h+5tbW1PB6PxpKAGUVFRRoaGjQ01LVr1/Pnz9PQEEB790lA29vbb9q0qeFJbbTNM7AKDYOgKVZWVomJiTQ0BNDefRLQ+MNTmrX1Qhx8srKyMjIyNTU1GLsJ0LQ2/8ge2ovs7Gx67qAJlrUDEA4CGv5F2x00IaRr166xsbH0tAXQfiGg4V80TCPkc3R0fPHiBT1tAbRfCGj4V15eHp130AhogGYJCOjg4OAnT57QXwowi7ZRHISQzz77LD8/n562ANovAQHN4/G8vLy6dOmyfv365ORk+msCRtD5ISEhRF1dvaioiLbmANojAQG9ffv29PT0TZs2PX/+vEuXLoMGDTpw4AB+lyReXl6etrY2bc2hlwOgWYL7oDkcjre39/Hjxx88eJCTk+Pv729oaOjv75+SkkJzfUAnGlZK4sPnhADNEvwLWVBQsHfvXnd3dzc3t549e96+fTsuLk5DQ8PT05Pm+oA2NE/od3R0xEg7gKYJ2FFlzJgxV69e7d+//+zZs0eOHKmkpEQd37JlCz1rNQD9amtraZ7X16lTp7dv39LZIkC7IyCge/XqtXPnTiMjo3rHZWVlMzMzaakK6Jabm9vWm13Vw+FwuFwubUvoAbRHAro4DAwM6qXz3r17qQeqqqp0FAW0o3MaIZ+VldX79+9pbhSgHREQ0CtXrqx3ZMmSJbQUA4zJzs7W19enuVFM+AZo2iddHI8fPyaEVFVVUQ8oCQkJ6urqdNcF9MrJyaH/DtrR0fHevXsjR46kuV2A9uKTgKZ+VbKysvi/M7Kysvr6+qGhoQyUBjTKysqi/w7ayckpPDyc5kYB2pFPAjo1NZUQMmfOnLCwMIbqAWbk5OR06NCB5kb19PSys7NpbhSgHfkvoB8/fmxhYaGnp+fv71+3i4Py+eef01sY0IqRPmhCiKqqaklJiZqaGv1NA7DffwHt6+sbEhIyZcoUX1/fhuclJSXRVxTQjs6Vkuqyt7d/9epVz5496W8agP3+C2h+BCOLpVBmZiZti0HX1bVr1+fPnyOgAQT6pIujifPQxSHZqqqqFBUV6W/X0dHx//7v/+hvF6Bd+KSLo4nzRLytvnbtWkJCwtixY9XV1X/55ZfExEQPD4+JEyeKck2QAF26dMGEb4DGCOjiELstW7b8/PPPqqqq27Zt8/b2Lisr43A4AQEB+fn5c+bMaaNGoUWYmm+toKBQWVnJSNMA7CdgFIfAvg5Rujh27tx55swZa2trQ0PD7t27T5gwgRAyePDgkJCQJgL60aNHf/31V72DsbGxNjY2ra4EBCooKNDS0mKqdRMTk5SUFDMzM6YKAGAtOkZxpKWl2dnZaWlp6ejo9O3blzo4ePDgadOmNfEqAwMDV1fXegdLSkqwHojY0byXSj0ODg4vXrxAQAM0RMcoDl1dXeoebebMmfw7tcLCQhUVlSZeZW5ubm5uXu9gXl5eTk6OeMuDzMxMAwMDplqnFoYePnw4UwUAsBYdO2iMHDmS2opl3bp1/GU9Ll682KNHDxpah2bl5OQwMsaOgq1VABojIKArKytDQkLs7e21tbXt7e3XrFlTVVUlShu//vqrm5tbvYPTp08/efKkKJcFccnKymIwoM3MzLA3MYBAAhbsnzdv3osXLzZs2GBubv7hw4e1a9empqaKfVEbrJDHHllZWb169WKqdRkZGQUFhaqqKgUFBaZqAGAnAQF9+vTp+Ph4an8NJyenvn37duzYEauOSTBm+6AJIXZ2dnFxcY6OjgzWAMBCAro4dHR06u4fyuPxaN4MCWjGbBcH+d9ADgYLAGCn/+6gX758ST2YO3ful19+uXjxYjMzs5SUlE2bNs2dO5eh8oAOTK2UxNe1a9eLFy8yWAAAO/0X0B4eHnW/MGvWLP7j9evXBwcH01cU0IvL5XI4Ajq7aNO1a9cNGzYwWAAAO/33a5mRkcFgHSDNNDU1CwsLma4CgHUE3zeVl5e/e/cuJyeH3xld7/4aJAaXy2XD8AktLS1mZ5wDsJCAgI6Kiho3bpyysnJ6erqJiUlSUhI+w5FgzM7z5uvateuLFy8ajpcHkGYCRnHMnz9/zZo1SUlJxsbG79+/P3PmjLe3N/2VAT0yMjIMDQ2ZruLfgGa6CgB2ERDQCQkJ/v7+hJCamhpCyMiRI589e0Z3XUCXzMxMRnYjrAcBDdCQgIDW1NTMzc0lhBgYGLx8+bK8vDwxMZH2woAmLLmDtrOzw8r9APUICOhp06bdvHmTEBIUFOTm5mZtbe3j40N7YUCTrKwsNtxBczgcLpdbd4YUAAj4kHDNmjXUgylTpvTu3buoqKjhuswgMTIyMlgyRMfCwuLDhw+WlpZMFwLAFs1MT7C1taWnDmAKS/qgyf/WHUVAA/DRsdwosBnjKyXxUSv3M10FAIswttwosER1dbW8vDzTVRBCiKOj44EDB5iuAoBFsNwosIWRkRHWGwCoC8uNSjW2LZOvqKhYUVHBdBUAbIHlRqVaRkaGkZER01X8x97e/tWrVxg1BEDBcqNSLSMjgyWfEFK6du0aGxuLgAagYLlRqZaenm5sbMx0Ff9xcnI6dOgQ01UAsIXgcdBPnz49evRoWlqaiYnJpEmTXFxcaC4L6MG2O2h7e/vXr18zXQUAWwj4kPDYsWPu7u4FBQX29vYFBQX9+/ePiIigvzKgAdv6oBUVFSsrK5muAoAtBNxB//jjj5cvX+avzDt16tSvv/563Lhx9BYGdPj48SOrApoQQn00bWZmxnQhAMwTcAedkZHRs2dP/tOePXuie1pSUXsyMF3FJ5ycnP7++2+mqwBgBQEB7erqun79ei6XSwjhcrlr1679/PPPaS8M6FBUVKSurs50FZ9wcXHB+uMAFAEBvWvXruPHj+vr63ft2lVfX//kyZO7du2ivzKQTs7OzghoAIqAPuiOHTu+fPny6dOn1Bisbt26ycnJ0V8ZtLWamhoWfmd1dXVzcnKYrgKAFeoHdHV1tbOz88uXL7t3785IQUAb9iw0Wo+2tnZ+fr62tjbThQAwrH4Xh7y8vIKCQnV1NSPVAJ3S0tJMTU2ZrkIAFxeXp0+fMl0FAPME9EEHBASMGTPm+vXrL168ePk/9FcGbS0jI4NV0wj5XF1dEdAApIktr7766qu6BzHSTvKkpqaybYwdxdXV9ciRI0xXAcA8AQGNLJYSHz9+dHBwYLoKAYyNjdPS0piuAoB5n3Rx5ObmBgYG9urVa+rUqenp6UzVBPSg1lphugrBtLW18/LymK4CgGGfBPTcuXMfP348atSopKSkKVOmMFUT0INtS9nV9fnnnz9+/JjpKgAY9kkXx/Xr1x8+fGhtbT1nzhw9PT327FZHj5ycnI8fP9bW1jo6OsrIyDBdTpurqKhQUlJiugrBevToERMTM3ToUKYLAWDSJwGdm5trYWFBCFFXV9fS0srLy2PVWpRtoaqqSl5eXkZGJjw8/Pr160ZGRpqamp06dVJSUgoLCzt27JiBgYGbm1tQUJA0RDZ79OjRA/NXAep/SHj06FFZWVlCSEVFxalTpzQ1NanjkydPpru0NlZTU7Njx46IiIgTJ06YmZnNmjWr7iYyhJA5c+bMmTMnMzPz+fPnVDpv377dzMzMy8uLtTeewistLVVRUWG6ikbp6OigDxrgk4C2t7fftGkT9djU1LTuLYyEBXRtba2Xl5eXl1d0dDSHI3jXAoqBgQH/D20fH5/jx49v3brVy8tr2bJltFTaVti/pKeVldU///xjbW3NdCEAjPkkm6RnQoqsrOzvv//e0g6cDh06LFu2bNmyZeXl5YSQ/Pz8o0ePTp48mf93RjvC5iEclN69e9+9excBDdJMwExCyZafn08NDxCle11ZWZkQoqGhoaqq6uPjM2/evHb393hqaio753nz9e3b9969e0xXAcAkqQvomTNnlpaWiuVScnJy06ZNi46OHjduHLV6SVVVlViuTAP2d3E4ODi8efOG6SoAmCRdAX38+HFra2t3d3fxXtbNzY26H9+yZYuPj8+dO3fEe/22wNqVkvhkZGS0tbWx9ChIM5oCOiEhISIiou4NUU1NTWhoKD2t8z19+nTVqlVtd/3vvvtux44dv//+e0hISNu1IhYpKSksD2hCiJubW3R0NNNVADCGjoA+d+6cg4PDihUrnJyc5s6dW1NTQwiprq5esGABDa3XtWnTprYeW2Zpabl79+6VK1cSQtLS0mJiYtq0uVYrKSlRU1NjuopmDBgw4NatW0xXAcAYOgJ65cqV27Zti4+P//Dhw6tXryZOnCjMetOnT58e0sCaNWsSEhJaUQOPx/v48WMrXigKBQWFsLCw0aNHx8bG0ty0ZHBxccEGsiDNmhoCLC7x8fGjR48mhBgZGV29etXX19fX1/fQoUNNv2rMmDFjxoypdzAiIqJ1nZKXLl168uRJm/ZvNKSnp/fbb7+9efNm27Ztv/76K3v2lyouLmbbXrECycrKmpiYsP/zTIA2QscdtKGhYXJyMvVYUVHx9OnTMjIyo0aNoqFpvsOHDzM116Zz587h4eFycnI8Hi8kJCQ7O5uRMupKTk6m5vSzn6en59WrV5muAoAZdAS0l5fXwYMH+U8VFBROnTqlp6dHQ9OUioqKjIwMxqc8yMjI9OjRY/To0WvXrqWmujAlOTm5vdyTenl5Xb58mekqAJhBR0Bv3bp17dq1dY9wOJyjR4++f/+ehtYJIfLy8jt37qSnraZ5enpGRUVZWFjw/6RgxIcPH8zNzRksQHiGhoYFBQVlZWVMFwLAADoCWkFBoWGPp5ycnKWlJQ2tU22xZ+sQWVnZyZMnd+rUiRCycePGP//8k/4a2lEXB0EvB0gxqZiocv78eaZLEMzf3//ChQve3t5v376ls93k5OT2cgdNCBk7duzJkyeZrgKAAZIf0Pn5+Xv37mW6CsH09PR27ty5efPmrKwsOttl814qDVlZWWVlZRUWFjJdCADdJD+gY2JievTowXQVTbGzs3NzcyOEnDhxYs2aNTT0t9bW1lKrfrcXEyZMOHr0KNNVANCtPf2Wts6LFy9cXV2ZrkIoY8eONTU1HTRo0KlTp9quFWoTmba7fluYOHHikSNHeDwe04UA0EryAzowMHDYsGFMVyEUWVnZadOm3bx5s00XmG6P8z7U1NT69u2L8XYgbSQ/oNXV1dkzhU8YqqqqQ4YMIYS8fv3az8+vdVPbm5CUlETb+BkxWrRo0caNG2tra5kuBIA+Eh7QNTU1Bw4cYLqKVurSpcu33347d+7cxYsXizGY2mlA6+vrDx8+PDw8vIlzamtrr1y5EhAQ4Obm5uHhMWDAAE9Pz127dmEYNbRTEh7QqampkZGRTFfRei4uLlevXh05cqQY9xRPSkrq0KGDuK5Gp8WLF58+ffrp06cNv1RVVbV3796+ffveuXNn0aJFt2/fvnHjRmRkZEREhKys7ODBgy9dukR/wQAikvCATkxMtLKyYroKUfXr109GRobL5Q4dOvTMmTMiXu39+/ftNKA5HM7hw4fnzZt3/fp1/sHCwsJt27a5u7uXlZXdvHlz7dq1Xbp04X9VQ0MjMDDw2rVrJ06coHmpLADRSXhAp6amMr4Eh7hwOJyIiIh79+4NHTo0LS2t1ddpX4Og6zEyMrp48eKpU6fc3d3HjRs3dOhQX19fNTW1yMjI4ODgxhb7VldXP3TokIyMTHBwMM0FA4hCpn0NXaKWG50zZ46Q53O5XBkZmfb1IWGzkpOTtbW1W71eqLu7e1RUlKhFHDxIamvJ9OmiXqe1qqqqsrKydHV1lZSUhH/VypUr5eTkcCsN7YWE30FzOBwJS2dCiLm5OZXOgYGBS5YsKSgoEP61ZWVlqqqqbVYafRQUFExNTVuUzoSQkJCQxMTEEydOtFFVAOIl4QG9c+dOCR6YtXv37t69e48YMUL4AcKJiYnttANaXHbv3h0WFhYXF8d0IQDNk/CAPnnyZPua09xSo0aNioyM7NevHyGkoqKi2Q4ryfjUVBRKSkr79+//+uuvq6qqmK4FoBmSHF6EEDGOTmMteXl5DQ0NQsj58+cHDhzY9C6rCGhCiLW19fTp01evXs10IQDNkPCAVlZWZroE+owbN+7YsWMnTpyYN29eY+f8888/EjOsRRTTp09/9erVkydPmC4EoCl0bBrLINauBN1GjIyM+HPtSkpK8vLy6q37jDtovp07d06ePPnmzZscjoT/FkD7JeF30O1u2TYxKiws/Prrr4OCguouNl1SUqKmpsZgVexhZmY2atQoluyFBiCQJAd0VlbWsWPHmK6CMSYmJlevXh0xYsT06dMrKioIIVwuF3eLdc2dO/ePP/74+PEj04UACCbJAf3hwweB6zZIlWHDhl26dIkaL7x9+3YTExOmK2IRDoezbt267777julCAAST5IDGn/P1pKenR0ZG/vrrrxhhxtevXz8ul/vgwQOmCwEQQJIDuqqqSktLi+kqWMTS0nLjxo2EEIxeqGvjxo3Lly9vX2segJSQ5B7JoUOHenh4MF0Fi8THx/fr18/Z2Zl6um/fPkVFRT8/P8mbDd8ipqam/fr1O3bsmJ+fH9O1AHxCku+gJW+ZJBElJCTY2Njwn06YMCElJaV///4XLlxgsCo2WLJkyY4dO8rLy5kuBOATkhzQ169ff/XqFdNVsEi9Tnk1NbXly5dfuXJFR0eHwarYQE1NbebMmdu2bWO6EIBPSHJAP3jwICMjg+kq2KKyslJBQaHhcQ0Njb59+xJC4uLi+vbte+TIkZqaGtqrY97UqVMvXbqUnZ3NdCEA/5HkgK6urpbmiSr1NDvJ287O7sqVK0lJSf379y8uLqatMJaQk5P74YcfsEAHsIokBzSHw1FUVGS6CrZ4+/Ztp06dmj5HQ0NjxYoV0dHR1HrTkZGRlZWVtFTHCkOHDk1OTn779i3ThQD8S5IDevny5T179mS6CrYQJqAp/E9W4+PjBwwYEBoaWlpa2palsQjmrQCrSHJAY1pzXXFxcXZ2di16ycyZM6OiotTU1G7cuNFGVbFN165d9fT0ml6yFYA2khzQp0+fTk5OZroKtkhKSrKwsGjpqxQUFGbMmPHll18SQs6dO7d48WJR9qttF0JCQlatWiXBG/FAOyLJAR0TE4N1cPhqa2tFHBX+5ZdfDhkyZMaMGbNnzxZXVSxkaGg4bNiwgwcPMl0IgEQHNI/Hk+z9roSXnp5ubGws+nWGDRt25cqV5cuXU09jY2NFvyYLLVy4cM+ePVI4lAXYRpLzi8PhCBz5K4Vev37dpUsXcV3NzMyMEMLj8fbt2zdw4MATJ05wuVxxXZwNlJWVFy5cuHbtWqYLAWknyQEdEhLi5OTEdBWs8ObNm86dO4v3mjIyMtu3bz99+vQ///xz79498V6ccWPHjn327Fl8fDzThYBUk+SAxigOPvHeQdelo6OzfPny/v37E0IOHz4cHByckJDQFg3Rb/PmzYsWLWK6CpBqkhzQx48fx4eElHfv3tna2rZ1K5MnTx41atR33303derUtm6LBg4ODra2tqdPn2a6EJBekhzQ9+/fr7sdnzSrrq6mpzt+wIABp06d2rNnDyGktrb28OHD7fqjttWrV2/evLldvwVo1yQ5oDGKg/Lx40dDQ0M6W6Rm2MvKylZUVAwfPjwoKKidjp5WV1dfsmTJihUrmC4EpJQk5xdGcVBevnzp4ODASNMzZsy4ffv22LFji4qKCCElJSXV1dWMVNJqo0aNysjIkLxPQaFdkOSA3rRpk5CrT0i2Fy9eMBXQFDc3N2oMyd27d93c3FauXNm+Znhu377922+/xXL+QD/GAprL5bb1qjQYxUF5+fKlo6Mj01UQQsiwYcPu3r3bo0ePNWvWMF1LCxgaGs6bN48/PQeANkwGNLWBadv5/fffc3Jy2rSJdiExMdHKyorpKv4lJyfn7e1NfYpICJk4ceL333+fmJjIbFXNmjBhQmZm5vXr15kuBKQLHfeYs2bNaniw2W07UlNT4+Li6h188eIFtVSxMO7cudOjRw9dXV0hz5dINTU1srKyrP2w9PDhw3/++eeSJUuGDx/u7+/PdDlNCQsL8/LycnJy0tfXZ7oWkBZ0BPT//d//jR8/XktLq+5BGRmZpl+Vlpb25MmTegcTExOb3hakLoziIITEx8fTMAK61eTk5IYPHz58+HDq6ZMnT/bv3z916tQePXowW1hDWlpaW7ZsmT59+oULF/BzBfSgI6Dt7e0nTJjg7e1d92BFRUV4eHgTr+rZs2fD5fYjIiKE77XAKA5CyPPnz1nSAS0MV1fX6urqAwcOLFiw4OzZs3p6ekxX9InevXt7eHisWrXqp59+YroWkAp03AhMnz694c5JHA6nrYeXbt++vRUrIEuYZ8+eOTs7M11FC/Tq1WvXrl1RUVFUOu/Zs+fIkSPs2dJlwYIFSUlJp06dYroQkAp0BHRwcPCYMWPqHeRwOG39UT5GcRBCYmNj29EdNB//ezdy5Mjs7OwRI0awZ7bInj17wsLCHj16xHQhIPkkuSvtwIEDhYWFTFfBsOLiYuE/VmUhfX39+fPnR0ZGUqPcqqqqli1b9uDBAwZLUlZWPnbsWFBQ0D///MNgGSANJDmgIyMjCwoKmK6CSWlpaWJZp58NVFVVCSEKCgpffvnlkSNHevfuzeCgNwMDg0OHDn311VftdAo7tBeS3AmAURx///13t27dmK5CzHr16tWrV6+amhpq28B79+5du3Zt7Nix9vb2dJZha2sbHh4+bty4U6dOGRkZ0dk0SA9Jzi95eXl5eXmmq2DSkydPJC+gKXJyctQ3t3v37j179ty8eXO/fv3y8vLorMHR0XHnzp2+vr4pKSl0tgvSQ5IDevfu3TSv4sY2T548cXV1ZbqKtiUvL+/l5XXgwIE7d+7o6OgQQjZv3rxixYqGg+jbgouLy549e8aNG/f27VsamgNpI8kBjVEc+fn52traTFdBt/nz5w8cOHD//v1ff/01Dc3Z29sfPXrU39//9u3bNDQHUkWSI2zPnj2TJk2iPlySQqmpqaampkxXwQAOh+Ph4eHh4cE/4u3traur+8UXX3h6eqqoqIi9xQ4dOly4cMHPz2/8+PHTp08X+/VBaknyHfRff/1VUlLCdBWMiYmJ6d69O9NVsMLFixe/++67+Pj4s2fPEkKqqqrEPvpCR0fnwoULjx49mjdvXrtb8xpYS5LvoGtra6V5FEdMTEy96fXSzM7Ozs7Ojnqck5Mzf/78rKysfv36zZs3T1wfVMjLy4eFhf3222/Dhg377bffzM3NxXJZkGaSnF/y8vLS3A0tDZ8Qto6xsfHJkyevX78+aNAgalXFu3fvHj58ODs7W/SLT5s2LTQ01M/Pj7pbBxCFJAf0wYMHpfAjMgqXy62qqlJWVma6EPZSUFAYPHiwiYkJIcTW1raoqGjGjBmDBw8Wfd0PR0fHP//88+LFi7Nnzy4rKxNHsSClJDmgpfn2uZ0uwcEUfX39OXPmnDt37ubNm9SnyuvWrRs1alRYWFjrNhNQVVXdt2/foEGDhgwZ8vTpU3HXC9JCkgM6LCys4Sp6UuLevXt9+vRhuop2bPny5eHh4RoaGocPH6aO/PXXX5mZmS26yNixYyMiIn744Yd169Y1u0MFQEOSHNDXrl2rqKhgugpm3Lt3r1+/fkxX0b4ZGBhMnjx55cqV1NOkpKRZs2a5ubnt3r1b+IuYmJhcvHhRVVV12LBhWFwJWkqSOwGkeRRHcnKymZkZ01VIFH9/f39//5qamqKiIkJIaWnpyJEjHRwcBgwYMGjQoCaWDJSRkQkODh4yZIi/v/+UKVMCAgJorBraN0nOLwUFBenshn7//n2HDh2YrkIyycnJUZ88q6qqXrlyZeLEie/evbt79y4hJDMz89SpUx8/fhT4wi5duly/fj0hIcHX1xd7GYOQJDmgjx8/Lp3DGKKiovr37890FZKPw+H06NHj22+/9fT0JIQoKSmlpaUFBQX169fv8ePHhJCamhoej8c/X0FBYf369UFBQT4+PtggHIQhyQEtnbfPhJDIyMgBAwYwXYXU0dTUDA4OPnny5J07dz7//HNCSFRUlJubm4+Pz7p164qLi6nT+vfvf+XKlf3793/77bdVVVWMlgxsJ8kBvX37dun86JzlO3lLj0GDBt25c+fgwYPdunWjPg757bffvvnmm3Pnzv34449dunQZOnQoPjmEJkhyQF++fJnL5TJdBd3i4+Otra2ZrgL+o6Oj4+npSQ2v/uqrrwIDA6uqqrZt2zZ58uTdu3d/+eWXixcvbqznGqScJHcC1NbWysjIMF0F3a5fvz5kyBCmqwDB5OTkHB0d+XOIOnXqdODAgeDg4DNnznTv3v348eOEkNjYWCMjI2pTc5ByknwHraSkJCcnx3QVdLtx4wYCuh3p3r37oeIfXgAAFHVJREFUvXv3NmzYkJaWRq36//Dhw8DAQDc3t6VLl1LnYO9jqSXJd9B//PGHtAV0dXV1bm6ulO8j0x6NHTvWxcXF399/9uzZM2fOnDlzJiGEv2zpt99+GxcXp6qqOmHChKlTpzJaKdBKkgNaCkdx3L59GxMI2ykbG5tr164tWLAgOjo6NDRUUVGRv6Pmnj17CCElJSXUHBkul+vt7V1RUWFlZeXn51d3awKQMJLcxREaGsp0CXS7ePHiiBEjmK4CWklJSWnXrl39+/cXOLpDTU3N2NiYEMLhcK5evXrr1q3ly5dbWVkRQgoKCgYNGjRs2LDg4GBqCDZIBkkO6HPnzjFdAt0ePHjQs2dPpqsAkUycOHHPnj3Tpk07depUE6fJyMjY2NhQAa2lpfXXX3+dPXt26tSp+vr6hJDk5GR3d3dPT88FCxa8fPmSptJB3KSuE0CCxcbG2tvbS1u3u0Tq1KnTtWvXgoKCIiMjN2/erKSkJMyrlJWVu3XrRj02NzePiooqLS2Ni4vT1dUlhLx8+XL27NmKiopWVlYLFy60s7OjZgngB4bNJPkOui22B2WzU6dO+fr6Ml0FiIeysvLevXv79OkzbNiwd+/ete4iqqqqrq6u1IfGDg4Ot2/fvnLlyqJFi6htCh4/fuzh4dG/f/9Ro0bFx8cTQgoLC9PT08X4LkBEMnXXCmC/iIiInJycOXPmCHMyl8uVqs8J+/btGxkZyf9kqW0dPEhqawl2sG578fHxM2fOnD59etuN38jLy9PQ0OBwOPfv39++fTuV0YcPHzYzM4uPj09JSbG2tjY1NcW9Nv0kOb+kKp0fP37s6OhIUzoDjWxtba9du7Z8+XI/P7+wsDAtLS2xN6Gjo0M96N27d+/evet+qbKy8vbt2wcPHkxLSzt27Jient61a9diY2M7dOhgbW3t7Ows9mKgLkmOsNDQ0Pnz5zNdBU0OHTr01VdfMV0FtAkFBYXNmzffuHFj+PDhP/300+DBg2lr2sHBwcHBoe4RZ2fnqqqqxMTE+/fvW1tbq6ur79mz5/Lly5aWljY2NoGBgfLy8tL2x2vbkeQujoEDB966dautS2KDiooKDw+PO3fu0NckujiYkJ+fP2/ePC0trQ0bNqipqTFdzn/y8/M/fPiQlpbm6ekpJyf366+/njx5UlZWVk1N7ezZs7Kyso8ePSoqKjI1NTU3N5fORYBbB//LSYKIiIgxY8YwXQW0OW1t7cOHD//xxx9DhgwJCQlhz5x+bW1tbW1tfo/HN99888033xBCuFwutYxfeXn53bt309LSSkpKjhw5QgjZsmXL27dvTUxMbG1tJ06cSAiprKxUVFRk7k2wkSQHtPSM4ti/f/+ZM2eYrgJoMnr06AEDBixevPjw4cM///wzNfCZnfgdHf3796+3icScOXOom+6SkhLqyM8//3zz5s2amhpzc3Nqr96IiIjy8nIDAwMbGxsbGxuai2cDSe7ikJKOsFu3bv3xxx87duygtVV0cbBAZGTkihUr/Pz8AgMDJfJHPSYm5vXr16mpqXJycsuWLSOELFq06NGjRxoaGi4uLj/99BMh5NatWzIyMnp6eqamppqamkyXLGYS+E3lk8gf2YZ+/vnnXbt2MV0FMGDAgAGRkZE7duwYMGDA999/T+28JUl69OjRo0ePukd++eUXQkhpaSn/vjsvL+/ly5dZWVmamprr1q0jhMyZMycuLs7Q0NDV1XXRokWEkFu3bsnJyX322WcmJiZtMQym7UhyhEnDKI6//vrL0tLSwsKC6UKAGfLy8gsXLpwyZcpPP/0UGhq6atWqeuPkJJKqqiq1AQIhZMyYMfU+gAkLC6uurs7Ozq6traWOpKWlxcfH5+TkGBgYrFy5khAyderUDx8+qKur9+nTh7o3P378OIfD+eyzz6ysrNjzCyXJXRwSP4qDy+UOGjQoIiKCgfVF0cXBPklJSSEhIVlZWUuWLMGuwcIoLi6urq6mhoFfvHgxKSkpNzfXxMRkxowZTJf2L0m+g5Z4oaGho0ePxurPQLG0tNy/f//79+83b968evXqwMDA0aNHY+5SE9TV1fmPvb29GaykMViLo716/vz5n3/+OW/ePKYLAXbp0KHDr7/+GhERkZiY2L9//xUrViQkJDBdFLSSJAe0BC83mp2dPWvWrP3792N5BBBIV1d32bJld+/e7dev3w8//DB48ODt27enpKQwXRe0jCR3cUjqKI6cnBxfX9/Q0FAzMzOmawFWk5WV9fLy8vLyKioqunDhwoIFC7Kzs93d3YcOHdqzZ0/0frCfJN9BS+SOKs+ePfPx8dm4cSMW5gfhaWhoTJo06dSpU9euXXNzczt//vyQIUO8vLxWr159+fLlrKwspgsEwWi6x6QWxHr16lVxcbG6urq9vf3UqVPd3NzatNFz585J0jC7jIyMTZs2vX379uTJk6ampkyXA+2SoqLikCFDqDnixcXFDx8+jImJOXDgQGZmpoqKip2dXadOnaiNWszMzBQUFJiuV9rREdDh4eFLliwZN27cpEmTNDU1CwsLnz9/PmLEiE2bNs2aNYuGAtqvkpKSuLi4hw8fXrt2rbq6+ptvvtmyZQvTRYGEUFdX9/Dw4O85W1ZWFhcX9+7du4cPHx4/fjwlJYXL5XK5XE1NTT09PX19/c8++0xHR0dTU1NLS0tLS0tVVVVZWVlTU1NeXp5VKzdJEjrGQRsbG0dERNTbbfr+/ftjx45NTU1t7FXnz5+n5uPXlZaW5ubmtmHDBmHatbGx4e8AxH6FhYXUuPqqqio5Obna2tra2lpNTc2OHTt269bNw8PDwMCA6RrrwDhoqVFSUpKRkZGdnZ2Xl5eXl1dQUFBYWFhSUpKfn19eXl5RUVFUVFRTU1NaWqqqqlpZWSkjI6OgoMDlcsvKyjQ0NKiLUGdqaWnJyMgI06iGhgazH4APHTqUDaOh6QhoFRWV5ORkamM0vvz8fDMzM/58zYaqq6sbfrW2tlZdXV3Iv7yon5tWFEw/GRkZGRkZeXn5djM0EAEN4lNSUlJdXc10FZ9QUVFhw9J6dHRx+Pj4TJgwYdWqVU5OTurq6sXFxbGxsatXr256ZLi8vLy2trYo7fL/9wYANkMPSWPoGMWxb98+S0tLT09PTU1NWVlZTU1NT0/PDh067N27l4bWAQDaKfrW4qiurk5KSiopKVFTU7O0tMQYzPYNXRwAbY++qRzy8vK2tra0NQcA0N5J8kQVAIB2DQENAMBSCGgAAJZCQAMAsBQCGgCApRDQAAAshYAGAGCpdrZpbIt8/vnnIk4WZ6f09HRNTU3+rsaMsC0uluHx3ol1Mn1VVVVGRoa5ubkYr8kS8fHxEjkJICsrS1FRUVNTk+lCxKympkZFReXixYtMFyLRO6qoq6tfv36d6SrEb9WqVYMHD5a8bZvfvn27devW8PBwpgsRv4EDB0rkj+LWrVutrKy+/PJLpgsRs6ysLJbs9okuDgAAlkJAAwCwFAIaAIClENAAACyFgAYAYClJDmgORzLHqMjKysrKSuA3TlLfF5HcH0U5OTlmdw5sI+z5UZTkcdDFxcXq6upMVyF+paWlysrKLPkBEi9qPwemqxA/Sf1RLC8vl5eXl8j/fljyLZPkgAYAaNck8C4MAEAyIKABAFgKAQ0AwFIIaAAAlkJAAwCwFAIaAIClENAAACwlCQFdXFw8YcIEVVVVU1PTxlYTFuYctmm25qqqqrlz51pbW6uoqDg5OZ0/f57+IltB+O9FUlKSioqKp6cnbbWJSMi3dujQoU6dOikqKnbq1OnRo0d0Vtg6wryv169fDxo0SF1d3cjIaPHixbW1tTQX2Qrbtm1zcXGRl5efNWtWY+cwHB289m/GjBkDBw7MysqKjo5WU1OLjo5u3Tls02zNRUVFc+fOffToUWZmZnh4uKKiYnx8PCOltojw3wtvb+9+/foNGzaMzvJEIcxbu3DhgoGBwfnz5zMzMx89evT+/Xvay2wxYd6Xi4tLQEBAaWnpu3fvLCws9uzZQ3+dLXXq1Knz589PmjQpMDCwsXOYjY52H9BVVVWqqqpRUVHU04CAgICAgFacwzatqNnW1vbEiRNtX5pIhH9fZ86c8fHxWb9+fXsJaCHfmouLy4EDB2itTDRCvi8tLS3+OTNmzAgODqavRNF88803jQU049HR7rs4kpKSSktLnZ2dqafOzs6vXr1qxTls09KaMzIykpKSunbtSkt1rSfk+yotLV26dGloaCi91YlEmLdWWVn57NmzjIwMExMTIyOjoKCgiooK2ittGSG/ZQsWLPj999/LysoSEhJu3rzZjjqmmsB4dLT7gC4pKSGE8Jc10dTULC4ubsU5bNOimisrKydOnPj111937tyZpvpaS8j3FRIS4ufnZ2VlRWtxohHmraWlpfF4vEuXLj19+jQmJiYqKmr9+vV0F9pCQn7Lhg8ffvv2bVVVVVtb2xEjRkhGQDMeHe0+oKnFz/j/aoWFhQ3XoBLmHLYRvubq6upx48bp6elt27aNvvpaS5j39fr167Nnzy5dupTu4kQjzFtTVlYmhCxevNjAwMDMzCwoKOjy5cs019lSwryvsrIyT0/PKVOmlJeXJycnP3nyZM2aNXQX2gYYj452H9CWlpYqKiqxsbHU0+fPn9vb27fiHLYRsmYulzthwgQej3fkyJF2sTKvMO8rOjo6NTXV0tLS0NBw7dq1t27dsrS0pLvQlhPmrRkZGenq6srIyNBeXesJ877S09Nzc3ODgoKUlJTMzMz8/PyuXr1Ke6Xix3x00Nnh3UYCAgKGDBmSl5d3//59DQ0N/sese/fuvXLlStPnsFmz74vL5Y4fP37gwIEFBQXl5eXl5eVcLpfRkoXS7PsqKyv7+D8rVqwYOHBgRkYGoyULS5gfxW+//dbNzS07OzstLc3Z2Xn16tXM1SusZt9XdXW1vr7+hg0bqqqq0tPT+/btO2fOHEZLFkp1dXV5efmsWbNmzJhRXl5eXV1NHWdPdEhCQBcVFY0bN05FRcXIyGjXrl3848OGDVuxYkXT57BZs+/r/fv39f673bp1K3P1CkuY7xdfOxrFwRPurVVUVMyYMUNDQ8PAwCA4OLiiooKhYltAmPf14MGDPn36qKur6+npTZo0KT8/n6FiW2DFihV1f32WLl1KHWdPdGDBfgAAlmr3fdAAAJIKAQ0AwFIIaAAAlkJAAwCwFAIaAIClENAAACyFgAYAYCkENAAASyGgAQBYCgENAMBSCGgAAJZCQAMAsBQCGgCApRDQAAAshYAGAGApBDQAAEshoAEAWAoBDQDAUghoaJcsLS0fP37Mhou0ETbXBrRBQEMLnD59ulevXioqKnp6eiNGjLh//35Lr2BqaiqW3AkJCbGwsBCx9dZdpC4HBweZOkR5a2KvDSQAAhqEtWfPnunTp/v7+8fHx8fHx0+fPv3gwYNMFTNlyhQ9PT02XGT//v3l/+Pq6so/zuVyGa8N2j2adxGHdqqsrExLS2v37t11D9bW1vJ4vPj4eA8PDy0tLTs7uxMnTlBfMjAw2LBhQ/fu3W1sbKZOnVpdXc3j8WbPni0nJ2dkZGRhYXHw4EEej/fDDz+Ym5urqan9fzv28pJaG4UBXI+peCmyTMsLibGh6IKXCgpsUE2KRgWFDQ5ESNggoQtEULOiWU0alEVRGBQFRf9A7KhJYDrNoqg0oYIyCzXDM9jgJ6ZhZN/ZHp7faLvc73rX6+Bxq0aj2d/fj66dm5sjCEIgEAwODl5dXTU0NAgEgra2Nr/fT91TXFx8fHycbKOEnT/uHm2S+hHilJeXr62txVaoVVqttrS0NNkB3W53Z2enRCLJy8vr6en5odngH4CAhpQcHBwwGIynp6e4ejgcLisrGx8fDwaDJEkKhUK73R6JRKRSaXt7eygUCoVCtbW1NpuNul8ul1O5Q1lfX/d6veFweGFhQSKRvL6+Umubmpru7u7Oz89zc3Pr6uqcTufz83N9ff3s7Cy1MDagE26UsHPc7lSTrx4hVsKAbm1tDQQC1LfXxzHe39+rq6vNZrPP5wsEAiRJJvxkvj8b/APwFwek5OHhQSAQ5OTkxNXtdrvX652YmOBwOAaDoaury2azUW8NDAyw2Ww2m93c3Gy32xO2NRqNUqmUxWKZTCYej3d6ekrVR0dHxWKxWq02GAyNjY1VVVVCobCjo+Pk5ORjk4QbJev80TePYDabxWKxWCw2GAxUxWKxcLlcJpOZcAyn0+lyuWZmZrKzs7lcbnTVT8wGmQ4BDSnJz89/eXnx+XxxdY/HI5fLs7KyqJcqlcrtdkeXUBc8Hs/v9ydsu7q6WlNTo1QqVSqVx+O5v7+n6oWFhdQFn8+PvU7YJ+FGyTp/9M0jTE1NORwOh8OxtbVFVYqKij454PX1tUKh4HK5yeZJ42yQ6bL+9gCQGfR6fW5u7sbGhslkihYjkYhMJnO73eFwmAqRy8tLuVz+SZ9fv/57JnC5XBaLhSTJyspKBoOhVqsjkUhapk3WOXb3qK8eIY5IJFIoFLEV6tk52RhKpfLm5iYUCnE4nNhVPzEbZDo8QUNKeDze9PT08PDw4uLi7e3t4+Pj9vZ2f3+/TqeTSqWTk5Nvb2+Hh4ebm5vd3d2f9JFIJGdnZ9S1z+fj8/kEQTAYjL29vYuLi3RNm6xz7O5RXz3CN8fQaDQEQQwNDfn9/mAwSP25///PBhkBAQ2p6uvrW1paslqtJSUlBEEsLy///v2bxWLt7u6SJFlQUNDb2zs/P6/T6T5pMjY2NjIyIhKJrFarXq83Go1arbalpeXo6KiioiJdoybrHLt79OavHuGbYzCZzJ2dHY/Ho1KpZDLZysrKX5kNMgIzXT8qAQAgvfAEDQBAUwhoAACaQkADANAUAhoAgKYQ0AAANIWABgCgKQQ0AABNIaABAGgKAQ0AQFMIaAAAmkJAAwDQFAIaAICmENAAADSFgAYAoCkENAAATSGgAQBoCgENAEBTCGgAAJr6A0ABYjWofeC6AAAAAElFTkSuQmCC\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "library(SoupX)\n",
    "sce = load10X('VEX1_RNAi_2_count6/outs/')\n",
    "sce = autoEstCont(sce, tfidfMin=0.85, forceAccept=TRUE)#, priorRhoStdDev = 0.3\n",
    "out = adjustCounts(sce, roundToInt=TRUE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2d5cceed",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                             est counts\n",
      "vsg-2-Tb427.BES40.22 0.036456257  63564\n",
      "rRNA-Tb927.2.1975    0.012574208  21924\n",
      "Tb927.1.2390         0.004678335   8157\n",
      "Tb927.5.1810         0.004315860   7525\n",
      "Tb11.v5.0498         0.002309057   4026\n",
      "Tb927.5.810          0.001885214   3287\n",
      "maxic-12S            0.001808933   3154\n",
      "Tb11.1810b           0.001710859   2983\n",
      "Tb11.v5.0381         0.001612784   2812\n",
      "Tb927.2.370          0.001586975   2767\n",
      "Tb927.10.8940        0.001434988   2502\n",
      "Tb927.6.560          0.001413193   2464\n",
      "Tb11.v5.0632         0.001395414   2433\n",
      "gene-Tb427.BES40.3   0.001371899   2392\n",
      "Tb927.5.1610         0.001320854   2303\n",
      "Tb927.11.9590        0.001297339   2262\n",
      "rRNA-Tb927.6.187     0.001261780   2200\n",
      "Tb927.3.3270         0.001240559   2163\n",
      "Tb927.6.4280         0.001216470   2121\n",
      "Tb927.9.12570        0.001175176   2049\n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "head(sce$soupProfile[order(sce$soupProfile$est, decreasing = TRUE), ], n = 20)\n",
    "#head(sce$soupProfile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c98c9f66",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Tb927.1.2390 beta tubulin\n",
    "#Tb927.1.2390 ysosomal/endosomal membrane protein p67\n",
    "#Tb11.v5.0498 lysosomal alpha-mannosidase precursor, putative\n",
    "#Tb927.10.8940 flagellum targeting protein kharon1, putative\n",
    "#Tb927.3.3270 ATP-dependent 6-phosphofructokinase, glycosomal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b067e666",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "74ceb2d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "plotChangeMap(sce, out, \"vsg-6-Tb427.BES15.12\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9d3971f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "plotChangeMap(sce, out, \"vsg-2-Tb427.BES40.22\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3dda676e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#%%R\n",
    "#vsgGenes = c(\"vsg-6-Tb427.BES15.12\", \"vsg-2-Tb427.BES40.22\")\n",
    "#useToEst = estimateNonExpressingCells(sce, nonExpressedGeneList = list(vsgGenes = vsgGenes))\n",
    "#sce = calculateContaminationFraction(sce, list(vsgGenes = vsgGenes), useToEst = useToEst)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "70e7e821",
   "metadata": {},
   "outputs": [],
   "source": [
    "#%%R\n",
    "#sce = calculateContaminationFraction(sce, \n",
    "#                                     list(vsgGenes = vsgGenes), \n",
    "#                                     useToEst = useToEst, forceAccept=TRUE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "77d262ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "#%%R\n",
    "#plotMarkerDistribution(sce)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0aa6b303",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "d24fbaa4",
   "metadata": {},
   "source": [
    "# Load dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "deb1f87c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "class: SingleCellExperiment \n",
      "dim: 11497 6762 \n",
      "metadata(0):\n",
      "assays(1): counts\n",
      "rownames(11497): gene-Tb427.BES40.1 gene-Tb427.BES40.2 ... Tb11.1770\n",
      "  Tb11.1800\n",
      "rowData names(0):\n",
      "colnames(6762): AAACCCAAGAGCATCG-1 AAACCCAAGTCCTGTA-1 ...\n",
      "  TTTGTTGGTATCGAGG-1 TTTGTTGTCACTCACC-1\n",
      "colData names(0):\n",
      "reducedDimNames(0):\n",
      "mainExpName: NULL\n",
      "altExpNames(0):\n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "sce <- SingleCellExperiment(assays = list(counts = out))\n",
    "sce"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b54b45a0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"counts\"\n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "assayNames(sce)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6c2c19c1-9baa-4789-92e2-0ac3cf3abe4c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4b420eb5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "hist(log(rowSums(counts(sce))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "89aef632-7a1b-4067-a7eb-4663ee069d83",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6f55ba6e-b657-489a-9684-33afeb92052a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7e9740e7-3398-4274-a1fc-3dd9ab413625",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AAACCCAAGAGCATCG-1 AAACCCAAGTCCTGTA-1 AAACCCAAGTCGCCCA-1 AAACCCAAGTCGGCCT-1 \n",
      "              TRUE               TRUE               TRUE               TRUE \n",
      "AAACCCACAATAGTGA-1 AAACCCACATATGGCT-1 \n",
      "              TRUE               TRUE \n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "head(colSums(counts(sce))>25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "a19ac0de",
   "metadata": {},
   "outputs": [],
   "source": [
    "#%%R\n",
    "#plotExprsFreqVsMean(sce)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7afbfd16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "ave.counts <- calculateAverage(sce)\n",
    "hist(log10(ave.counts), breaks=100, main=\"\", col=\"grey80\", \n",
    "    xlab=expression(Log[10]~\"average count\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "730d3638",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "num.cells <- nexprs(sce, byrow=TRUE)\n",
    "smoothScatter(log10(ave.counts), num.cells, ylab=\"Number of cells\", \n",
    "    xlab=expression(Log[10]~\"average count\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e703163c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "plotHighestExprs(sce,  as_percentage = TRUE)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e8eb582",
   "metadata": {},
   "source": [
    "# Add QC \n",
    "Default testing sum and detected transcripts plus:\n",
    "- maxicircle\n",
    "- ribosomal RNA\n",
    "- VSGs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f084ab2d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DataFrame with 6 rows and 11 columns\n",
      "                         sum  detected subsets_Mito_sum subsets_Mito_detected\n",
      "                   <numeric> <integer>        <numeric>             <integer>\n",
      "AAACCCAAGAGCATCG-1       415       310                4                     2\n",
      "AAACCCAAGTCCTGTA-1       462       391               11                     7\n",
      "AAACCCAAGTCGCCCA-1       729       574                4                     2\n",
      "AAACCCAAGTCGGCCT-1       674       479               12                     3\n",
      "AAACCCACAATAGTGA-1       610       457               12                     5\n",
      "AAACCCACATATGGCT-1       449       340                4                     1\n",
      "                   subsets_Mito_percent subsets_VSG_sum subsets_VSG_detected\n",
      "                              <numeric>       <numeric>            <integer>\n",
      "AAACCCAAGAGCATCG-1             0.963855              13                    1\n",
      "AAACCCAAGTCCTGTA-1             2.380952               0                    0\n",
      "AAACCCAAGTCGCCCA-1             0.548697               0                    0\n",
      "AAACCCAAGTCGGCCT-1             1.780415              37                    2\n",
      "AAACCCACAATAGTGA-1             1.967213              50                    2\n",
      "AAACCCACATATGGCT-1             0.890869              18                    1\n",
      "                   subsets_VSG_percent subsets_Ribo_sum subsets_Ribo_detected\n",
      "                             <numeric>        <numeric>             <integer>\n",
      "AAACCCAAGAGCATCG-1             3.13253               58                     3\n",
      "AAACCCAAGTCCTGTA-1             0.00000               19                     2\n",
      "AAACCCAAGTCGCCCA-1             0.00000               75                     4\n",
      "AAACCCAAGTCGGCCT-1             5.48961               45                     5\n",
      "AAACCCACAATAGTGA-1             8.19672               37                     4\n",
      "AAACCCACATATGGCT-1             4.00891               56                     6\n",
      "                   subsets_Ribo_percent\n",
      "                              <numeric>\n",
      "AAACCCAAGAGCATCG-1             13.97590\n",
      "AAACCCAAGTCCTGTA-1              4.11255\n",
      "AAACCCAAGTCGCCCA-1             10.28807\n",
      "AAACCCAAGTCGGCCT-1              6.67656\n",
      "AAACCCACAATAGTGA-1              6.06557\n",
      "AAACCCACATATGGCT-1             12.47216\n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "is.mito <- grepl(\"^maxic\", rownames(sce))\n",
    "is.vsg <- grepl(\"^vsg-\", rownames(sce))\n",
    "is.Ribo <-grepl(\"^rRNA-\", rownames(sce)) \n",
    "df <- perCellQCMetrics(counts(sce), subsets=list(Mito=is.mito, VSG=is.vsg, Ribo=is.Ribo))\n",
    "head(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "07717eb5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#%%R\n",
    "#sce <- perCellQCMetrics(sce, subsets=list(vsg=is.vsg, Mt=is.mito, Ribo=is.Ribo))\n",
    "\n",
    "#par(mfrow=c(2,2), mar=c(5.1, 4.1, 0.1, 0.1))\n",
    "#hist(sce$total_counts/1e3, xlab=\"Library sizes (thousands)\", main=\"\", \n",
    "#    breaks=20, col=\"grey80\", ylab=\"Number of cells\")\n",
    "#hist(sce$total_features, xlab=\"Number of expressed genes\", main=\"\", \n",
    "#    breaks=20, col=\"grey80\", ylab=\"Number of cells\")\n",
    "#hist(sce$pct_counts_Ribo, xlab=\"ERCC proportion (%)\",\n",
    "#    ylab=\"Number of cells\", breaks=20, main=\"\", col=\"grey80\")\n",
    "#hist(sce$pct_counts_Mt, xlab=\"Mitochondrial proportion (%)\", \n",
    "#    ylab=\"Number of cells\", breaks=20, main=\"\", col=\"grey80\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "9a5947cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "#%%R\n",
    "#sce$pct_counts_Ribo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "0dfc744b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#%%R\n",
    "#sum(is.Ribo)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c43f3fa",
   "metadata": {},
   "source": [
    "# Test x outlayers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "d524ce37",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] 2050\n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "# not too high / not too low\n",
    "qc.lib2 <- isOutlier(df$sum, nmads = 1, log=TRUE, type=\"lower\")\n",
    "qc.lib2b <- isOutlier(df$sum, nmads = 3, log=TRUE, type=\"higher\")\n",
    "qc.nexprs2 <- isOutlier(df$detected, nmads = 1, log=TRUE, type=\"lower\")\n",
    "qc.vsg2 <- isOutlier(df$subsets_VSG_percent, nmads = 1, type=\"lower\")\n",
    "\n",
    "# not too high\n",
    "qc.mito2 <- isOutlier(df$subsets_Mito_percent, nmads = 2, type=\"higher\")\n",
    "qc.ribo2 <- isOutlier(df$subsets_Ribo_percent, nmads = 2, type=\"higher\")\n",
    "\n",
    "discard2 <- qc.lib2 | qc.nexprs2 | qc.mito2 | qc.ribo2 | qc.vsg2 | qc.lib2b\n",
    "sum(discard2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6069424",
   "metadata": {},
   "source": [
    "## add discarded info to the sce object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "78b856c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <span>BoolVector with 6762 elements.</span>\n",
       "        <table>\n",
       "        <tbody>\n",
       "          <tr>\n",
       "          \n",
       "            <td>\n",
       "                   1\n",
       "            </td>\n",
       "          \n",
       "            <td>\n",
       "                   1\n",
       "            </td>\n",
       "          \n",
       "            <td>\n",
       "                   1\n",
       "            </td>\n",
       "          \n",
       "            <td>\n",
       "            ...\n",
       "            </td>\n",
       "          \n",
       "            <td>\n",
       "                   0\n",
       "            </td>\n",
       "          \n",
       "            <td>\n",
       "                   0\n",
       "            </td>\n",
       "          \n",
       "            <td>\n",
       "                   1\n",
       "            </td>\n",
       "          \n",
       "          </tr>\n",
       "        </tbody>\n",
       "        </table>\n",
       "        "
      ],
      "text/plain": [
       "<rpy2.robjects.vectors.BoolVector object at 0x2b8141197480> [RTYPES.LGLSXP]\n",
       "R classes: ('logical',)\n",
       "[       1,        1,        1,        0, ...,        0,        0,        0,        1]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%R sce$discard_mito <- qc.mito2\n",
    "%R sce$discard_sum <- qc.lib2\n",
    "%R sce$discard_sum2 <- qc.lib2b\n",
    "%R sce$discard_detect <- qc.nexprs2\n",
    "%R sce$discard_vsg <- qc.vsg2\n",
    "%R sce$discard_ribo <- qc.ribo2\n",
    "\n",
    "%R sce$discard_all <- discard2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62cc7c4b",
   "metadata": {},
   "source": [
    "## quick add qc to sce"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "31772f93",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "class: SingleCellExperiment \n",
      "dim: 11497 6762 \n",
      "metadata(0):\n",
      "assays(1): counts\n",
      "rownames(11497): gene-Tb427.BES40.1 gene-Tb427.BES40.2 ... Tb11.1770\n",
      "  Tb11.1800\n",
      "rowData names(0):\n",
      "colnames(6762): AAACCCAAGAGCATCG-1 AAACCCAAGTCCTGTA-1 ...\n",
      "  TTTGTTGGTATCGAGG-1 TTTGTTGTCACTCACC-1\n",
      "colData names(19): discard_mito discard_sum ... subsets_Ribo_percent\n",
      "  total\n",
      "reducedDimNames(0):\n",
      "mainExpName: NULL\n",
      "altExpNames(0):\n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "sce <- addPerCellQC(sce, subsets=list(Mito=is.mito, VSG=is.vsg, Ribo=is.Ribo))\n",
    "sce"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "6927cf10-6d26-47d0-b329-f238bdcc3f49",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "class: SingleCellExperiment \n",
      "dim: 11497 4712 \n",
      "metadata(0):\n",
      "assays(1): counts\n",
      "rownames(11497): gene-Tb427.BES40.1 gene-Tb427.BES40.2 ... Tb11.1770\n",
      "  Tb11.1800\n",
      "rowData names(0):\n",
      "colnames(4712): AAACCCAAGTCGGCCT-1 AAACCCACAATAGTGA-1 ...\n",
      "  TTTGTTGCATGACTGT-1 TTTGTTGGTATCGAGG-1\n",
      "colData names(19): discard_mito discard_sum ... subsets_Ribo_percent\n",
      "  total\n",
      "reducedDimNames(0):\n",
      "mainExpName: NULL\n",
      "altExpNames(0):\n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "sce <- sce[, which(!discard2)]\n",
    "sce"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c8324309-2857-4d3e-b6b4-fb11941e731d",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "5cbf8c03-52ad-48a4-9820-542ec4fc79de",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%R\n",
    "#is.vsg6 <- grepl(\"^vsg-6-\", rownames(sce))\n",
    "#is.vsg8 <- grepl(\"^vsg-8-\", rownames(sce))\n",
    "#is.vsg15 <- grepl(\"^vsg-15-\", rownames(sce))\n",
    "#is.vsg17 <- grepl(\"^vsg-17-\", rownames(sce))\n",
    "is.vsg <- grepl(\"^vsg-\", rownames(sce))\n",
    "#is.vsg <- is.vsg6 | is.vsg8 | is.vsg15 | is.vsg17 | is.vsg2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bc1d36a6-6180-4998-a1c8-7f1845d52e27",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "863fe9f7-7273-44ee-881a-0b21ed26016d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "class: SingleCellExperiment \n",
      "dim: 22 4712 \n",
      "metadata(0):\n",
      "assays(1): counts\n",
      "rownames(22): vsg-2-Tb427.BES40.22 vsg-9-Tb427.BES129.14 ...\n",
      "  vsg-mes-Tb427VSG-559 vsg-mes-Tb427VSG-3591\n",
      "rowData names(0):\n",
      "colnames(4712): AAACCCAAGTCGGCCT-1 AAACCCACAATAGTGA-1 ...\n",
      "  TTTGTTGCATGACTGT-1 TTTGTTGGTATCGAGG-1\n",
      "colData names(19): discard_mito discard_sum ... subsets_Ribo_percent\n",
      "  total\n",
      "reducedDimNames(0):\n",
      "mainExpName: NULL\n",
      "altExpNames(0):\n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "\n",
    "#is.vsg <- grepl(\"^vsg-\", rownames(sce))\n",
    "sce_vsg <- sce[which(is.vsg), ]\n",
    "sce_vsg\n",
    "#sce_vsg <- SingleCellExperiment(assays = list(counts = counts(sce_vsg))\n",
    "\n",
    "#sce_vsg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "b2d4123b-e172-4c59-a5d4-ef3bbad22de6",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%R\n",
    "test <- as.matrix(counts(sce_vsg))\n",
    "write.table(test,file=paste(\"temp_count_vsg_vex1_2.csv\",sep=''),sep = \",\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "46d923d3-7bc5-4b2f-bb60-9fb906117406",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAACCCAAGTCGGCCT-1</th>\n",
       "      <th>AAACCCACAATAGTGA-1</th>\n",
       "      <th>AAACCCACATATGGCT-1</th>\n",
       "      <th>AAACCCAGTCCGTTTC-1</th>\n",
       "      <th>AAACCCATCTTCTGTA-1</th>\n",
       "      <th>AAACGAAAGAAAGCGA-1</th>\n",
       "      <th>AAACGAACAGGTCAGA-1</th>\n",
       "      <th>AAACGAACATAGGTAA-1</th>\n",
       "      <th>AAACGAAGTACAGTAA-1</th>\n",
       "      <th>AAACGAAGTAGATCGG-1</th>\n",
       "      <th>...</th>\n",
       "      <th>TTTGGAGCAAGCTGCC-1</th>\n",
       "      <th>TTTGGTTAGGCTTAAA-1</th>\n",
       "      <th>TTTGGTTCAACTCATG-1</th>\n",
       "      <th>TTTGGTTCACGGGTAA-1</th>\n",
       "      <th>TTTGGTTGTCGGAAAC-1</th>\n",
       "      <th>TTTGGTTGTGCTGCAC-1</th>\n",
       "      <th>TTTGTTGAGCCGATAG-1</th>\n",
       "      <th>TTTGTTGCAACGGGTA-1</th>\n",
       "      <th>TTTGTTGCATGACTGT-1</th>\n",
       "      <th>TTTGTTGGTATCGAGG-1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>vsg-2-Tb427.BES40.22</th>\n",
       "      <td>36</td>\n",
       "      <td>49</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>48</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>52</td>\n",
       "      <td>111</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>93</td>\n",
       "      <td>86</td>\n",
       "      <td>19</td>\n",
       "      <td>17</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>67</td>\n",
       "      <td>28</td>\n",
       "      <td>18</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vsg-9-Tb427.BES129.14</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>vsg-6-Tb427.BES15.12</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vsg-21-Tb427.BES28.15</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vsg-18-Tb427.BES98.12</th>\n",
       "      <td>0</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 4712 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       AAACCCAAGTCGGCCT-1  AAACCCACAATAGTGA-1  \\\n",
       "vsg-2-Tb427.BES40.22                   36                  49   \n",
       "vsg-9-Tb427.BES129.14                   0                   0   \n",
       "vsg-6-Tb427.BES15.12                    0                   0   \n",
       "vsg-21-Tb427.BES28.15                   0                   0   \n",
       "vsg-18-Tb427.BES98.12                   0                   0   \n",
       "\n",
       "                       AAACCCACATATGGCT-1  AAACCCAGTCCGTTTC-1  \\\n",
       "vsg-2-Tb427.BES40.22                   18                  18   \n",
       "vsg-9-Tb427.BES129.14                   0                   0   \n",
       "vsg-6-Tb427.BES15.12                    0                   0   \n",
       "vsg-21-Tb427.BES28.15                   0                   0   \n",
       "vsg-18-Tb427.BES98.12                   0                   0   \n",
       "\n",
       "                       AAACCCATCTTCTGTA-1  AAACGAAAGAAAGCGA-1  \\\n",
       "vsg-2-Tb427.BES40.22                   48                  10   \n",
       "vsg-9-Tb427.BES129.14                   0                   0   \n",
       "vsg-6-Tb427.BES15.12                    0                   0   \n",
       "vsg-21-Tb427.BES28.15                   0                   0   \n",
       "vsg-18-Tb427.BES98.12                   0                   0   \n",
       "\n",
       "                       AAACGAACAGGTCAGA-1  AAACGAACATAGGTAA-1  \\\n",
       "vsg-2-Tb427.BES40.22                    9                  52   \n",
       "vsg-9-Tb427.BES129.14                   0                   0   \n",
       "vsg-6-Tb427.BES15.12                    0                   0   \n",
       "vsg-21-Tb427.BES28.15                   0                   0   \n",
       "vsg-18-Tb427.BES98.12                   0                   0   \n",
       "\n",
       "                       AAACGAAGTACAGTAA-1  AAACGAAGTAGATCGG-1  ...  \\\n",
       "vsg-2-Tb427.BES40.22                  111                   6  ...   \n",
       "vsg-9-Tb427.BES129.14                   0                   0  ...   \n",
       "vsg-6-Tb427.BES15.12                    0                   0  ...   \n",
       "vsg-21-Tb427.BES28.15                   0                   0  ...   \n",
       "vsg-18-Tb427.BES98.12                   0                   0  ...   \n",
       "\n",
       "                       TTTGGAGCAAGCTGCC-1  TTTGGTTAGGCTTAAA-1  \\\n",
       "vsg-2-Tb427.BES40.22                   93                  86   \n",
       "vsg-9-Tb427.BES129.14                   0                   0   \n",
       "vsg-6-Tb427.BES15.12                    0                   0   \n",
       "vsg-21-Tb427.BES28.15                   0                   0   \n",
       "vsg-18-Tb427.BES98.12                   0                   0   \n",
       "\n",
       "                       TTTGGTTCAACTCATG-1  TTTGGTTCACGGGTAA-1  \\\n",
       "vsg-2-Tb427.BES40.22                   19                  17   \n",
       "vsg-9-Tb427.BES129.14                   0                   0   \n",
       "vsg-6-Tb427.BES15.12                    0                   0   \n",
       "vsg-21-Tb427.BES28.15                   0                   0   \n",
       "vsg-18-Tb427.BES98.12                   0                   0   \n",
       "\n",
       "                       TTTGGTTGTCGGAAAC-1  TTTGGTTGTGCTGCAC-1  \\\n",
       "vsg-2-Tb427.BES40.22                    6                  20   \n",
       "vsg-9-Tb427.BES129.14                   0                   0   \n",
       "vsg-6-Tb427.BES15.12                    0                   0   \n",
       "vsg-21-Tb427.BES28.15                   0                   0   \n",
       "vsg-18-Tb427.BES98.12                   0                   0   \n",
       "\n",
       "                       TTTGTTGAGCCGATAG-1  TTTGTTGCAACGGGTA-1  \\\n",
       "vsg-2-Tb427.BES40.22                   67                  28   \n",
       "vsg-9-Tb427.BES129.14                   0                   0   \n",
       "vsg-6-Tb427.BES15.12                    0                   0   \n",
       "vsg-21-Tb427.BES28.15                   0                   0   \n",
       "vsg-18-Tb427.BES98.12                   0                   0   \n",
       "\n",
       "                       TTTGTTGCATGACTGT-1  TTTGTTGGTATCGAGG-1  \n",
       "vsg-2-Tb427.BES40.22                   18                  10  \n",
       "vsg-9-Tb427.BES129.14                   0                   0  \n",
       "vsg-6-Tb427.BES15.12                    0                   0  \n",
       "vsg-21-Tb427.BES28.15                   0                   0  \n",
       "vsg-18-Tb427.BES98.12                   0                   0  \n",
       "\n",
       "[5 rows x 4712 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_count = pd.read_csv('temp_count_vsg_vex1_2.csv')\n",
    "temp_count.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "025a4666-c57d-49ea-9a31-38de793c7609",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "vsg-9-Tb427.BES129.14          0\n",
       "vsg-19-Tb427.BES10.10          0\n",
       "vsg-mes-Tb427VSG-559           0\n",
       "vsg-mes-Tb427VSG-639           2\n",
       "vsg-13-Tb427.BES51.12          7\n",
       "vsg-18-Tb427.BES98.12          9\n",
       "vsg-mes-Tb427VSG-1954         24\n",
       "vsg-mes-Tb427VSG-636          26\n",
       "vsg-mes-Tb427VSG-653          32\n",
       "vsg-16-Tb427.BES122.11        33\n",
       "vsg-21-Tb427.BES28.15         33\n",
       "vsg-mes-Tb427VSG-3591         80\n",
       "vsg-mes-Tb427VSG-397         108\n",
       "vsg-11-Tb427.BES126.15       131\n",
       "vsg-3-Tb427.BES65.13         221\n",
       "vsg-14-Tb427.BES64.2         223\n",
       "vsg-mes-Tb427VSG-531         240\n",
       "vsg-15-Tb427.BES134.6        366\n",
       "vsg-17-Tb427.BES56.13        593\n",
       "vsg-6-Tb427.BES15.12         930\n",
       "vsg-8-Tb427.BES29.9         2743\n",
       "vsg-2-Tb427.BES40.22      112625\n",
       "dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_count.sum(axis=1).sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "25c8c4ff-7410-4c1b-86e1-102ccbbbdb33",
   "metadata": {},
   "outputs": [],
   "source": [
    "#is.vsg16 <- grepl(\"^vsg-16-\", rownames(sce_vsg))\n",
    "#is.vsg21 <- grepl(\"^vsg-21-\", rownames(sce_vsg))\n",
    "#is.mes639 <- grepl(\"^vsg-mes-Tb427VSG-639\", rownames(sce_vsg))\n",
    "##is.mes636 <- grepl(\"^vsg-mes-Tb427VSG-636\", rownames(sce_vsg))\n",
    "#| is.vsg16 | is.vsg21 | is.mes639 | is.mes636"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "c23a55c3-907e-4f5b-961f-e347f2ef6ed5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\n%%R\\n\\nis.vsg16 <- grepl(\"^vsg-16-\", rownames(sce_vsg))\\nis.vsg19 <- grepl(\"^vsg-19-\", rownames(sce_vsg))\\nis.vsg21 <- grepl(\"^vsg-21-\", rownames(sce_vsg))\\nis.mes559 <- grepl(\"^vsg-mes-Tb427VSG-559\", rownames(sce_vsg))\\nis.mes639 <- grepl(\"^vsg-mes-Tb427VSG-639\", rownames(sce_vsg))\\nis.mes636 <- grepl(\"^vsg-mes-Tb427VSG-636\", rownames(sce_vsg))\\nis.vsg9 <- grepl(\"^vsg-9-\", rownames(sce_vsg))\\nis.vsg13 <- grepl(\"^vsg-13-\", rownames(sce_vsg))\\nis.vsg18 <- grepl(\"^vsg-18-\", rownames(sce_vsg))\\n\\n\\ndiscard <- is.vsg16  | is.vsg19  | is.vsg21 | is.mes559 | is.mes639 | is.mes636 | is.vsg9 | is.vsg13 | is.vsg18 \\n\\nretain <- !discard\\nhead(retain)\\n\\nsce_vsg <- sce_vsg[which(retain), ]\\nsce_vsg\\n'"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''\n",
    "%%R\n",
    "\n",
    "is.vsg16 <- grepl(\"^vsg-16-\", rownames(sce_vsg))\n",
    "is.vsg19 <- grepl(\"^vsg-19-\", rownames(sce_vsg))\n",
    "is.vsg21 <- grepl(\"^vsg-21-\", rownames(sce_vsg))\n",
    "is.mes559 <- grepl(\"^vsg-mes-Tb427VSG-559\", rownames(sce_vsg))\n",
    "is.mes639 <- grepl(\"^vsg-mes-Tb427VSG-639\", rownames(sce_vsg))\n",
    "is.mes636 <- grepl(\"^vsg-mes-Tb427VSG-636\", rownames(sce_vsg))\n",
    "is.vsg9 <- grepl(\"^vsg-9-\", rownames(sce_vsg))\n",
    "is.vsg13 <- grepl(\"^vsg-13-\", rownames(sce_vsg))\n",
    "is.vsg18 <- grepl(\"^vsg-18-\", rownames(sce_vsg))\n",
    "\n",
    "\n",
    "discard <- is.vsg16  | is.vsg19  | is.vsg21 | is.mes559 | is.mes639 | is.mes636 | is.vsg9 | is.vsg13 | is.vsg18 \n",
    "\n",
    "retain <- !discard\n",
    "head(retain)\n",
    "\n",
    "sce_vsg <- sce_vsg[which(retain), ]\n",
    "sce_vsg\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "2352ac2c-844d-4014-b877-677f81241ec4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\n%%R\\nkeep_feature <- colSums(counts(sce_vsg)) > 25\\nsce_vsg <- sce_vsg[, keep_feature]\\nsce_vsg\\n'"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''\n",
    "%%R\n",
    "keep_feature <- colSums(counts(sce_vsg)) > 25\n",
    "sce_vsg <- sce_vsg[, keep_feature]\n",
    "sce_vsg\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3f818346-8504-48be-9f0b-acfee51b6a9a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "b1b6d00e-b7dc-47ee-949f-137bafbb9f01",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "class: SingleCellExperiment \n",
      "dim: 22 4712 \n",
      "metadata(0):\n",
      "assays(1): counts\n",
      "rownames(22): vsg-2-Tb427.BES40.22 vsg-9-Tb427.BES129.14 ...\n",
      "  vsg-mes-Tb427VSG-559 vsg-mes-Tb427VSG-3591\n",
      "rowData names(0):\n",
      "colnames(4712): AAACCCAAGTCGGCCT-1 AAACCCACAATAGTGA-1 ...\n",
      "  TTTGTTGCATGACTGT-1 TTTGTTGGTATCGAGG-1\n",
      "colData names(19): discard_mito discard_sum ... subsets_Ribo_percent\n",
      "  total\n",
      "reducedDimNames(0):\n",
      "mainExpName: NULL\n",
      "altExpNames(0):\n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "#sce_vsg <- SingleCellExperiment(assays = list(counts = as.matrix(counts(sce_vsg)))\n",
    "sce_vsg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "608f0806-3d0b-41e4-ba65-561e0ab9d1eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%R\n",
    "saveRDS(sce_vsg, paste(\"sce_vsg_vex1_2.rds\",sep=''))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "47a91cda-dc14-4956-a2f1-74aadaf3da5f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "a0efcd96-00ce-46a2-9627-9a915b74e7cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "class: SingleCellExperiment \n",
      "dim: 22 708 \n",
      "metadata(0):\n",
      "assays(1): counts\n",
      "rownames(22): vsg-2-Tb427.BES40.22 vsg-9-Tb427.BES129.14 ...\n",
      "  vsg-mes-Tb427VSG-559 vsg-mes-Tb427VSG-3591\n",
      "rowData names(0):\n",
      "colnames(708): AAACCCACAATAGTGA-1 AAACCCATCTTCTGTA-1 ...\n",
      "  TTTGGTTAGGCTTAAA-1 TTTGTTGAGCCGATAG-1\n",
      "colData names(19): discard_mito discard_sum ... subsets_Ribo_percent\n",
      "  total\n",
      "reducedDimNames(0):\n",
      "mainExpName: NULL\n",
      "altExpNames(0):\n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "keep_feature <- colSums(counts(sce_vsg)) > 45\n",
    "sce_vsg <- sce_vsg[, keep_feature]\n",
    "sce_vsg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f092936b-324e-4e15-90c5-15ca2bd23729",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8013"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2544+3084+1677+708"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dba21107-10a7-4ed7-80c9-cdd3c1db6f14",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3405e76b-32ef-4e21-88a0-31618330d1da",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "04497465-4494-406e-b046-b7d6fba9879d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "942b0720-2336-4a40-9127-483dca0c2765",
   "metadata": {},
   "outputs": [],
   "source": [
    "#%%R\n",
    "#test <- as.matrix(counts(sce_vsg))\n",
    "#write.table(test,file=paste(\"new_count_vsg_vex2_1_681517.csv\",sep=''),sep = \",\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "bfef3c35-ca0b-436b-9e17-073ddc8637dc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"counts\"    \"logcounts\"\n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "#clust.sce <- quickCluster(sce_vsg)\n",
    "sce_vsg <- computeSumFactors(sce_vsg)#, cluster=clust.sce, min.mean=0.1)\n",
    "sce_vsg <- logNormCounts(sce_vsg)\n",
    "assayNames(sce_vsg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2764ee75-0a9b-43eb-ac65-b37c0a996e5e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ae97645d-340f-486c-9d46-d3b7430739ba",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a15e167d-c74c-4174-8a4c-cc109247659f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0b78f34a-77fe-4b0b-b1b3-7cb3be52afe7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fab0153f-0733-4637-913b-6d0124ad7f81",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "c96e8557-4f0f-4a5c-bb83-bfa25b5fd516",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%R\n",
    "test <- as.matrix(counts(sce_vsg))\n",
    "write.table(test,file=paste(\"new_count_vsg_vex1_2.csv\",sep=''),sep = \",\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "c561bf0e-9613-4a08-a8ee-5105b50452af",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%R\n",
    "test <- as.matrix(logcounts(sce_vsg))\n",
    "write.table(test,file=paste(\"new_count_vsg_vex1_2_norm.csv\",sep=''),sep = \",\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "3300ca32-ab76-482e-8439-412a783a0158",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "sce_vsg <- runUMAP(sce_vsg)\n",
    "#sce_vsg\n",
    "plotReducedDim(sce_vsg, dimred=\"UMAP\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "85857abc-3d53-4d04-ba8f-f75ed7e3fd49",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e11bb11a-278f-4315-80ac-1221d59a2470",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8ca98181-d61b-4b3f-a54f-86b7b6c1a7fb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "c5e5a49d-6b9b-45e9-b93d-216ca8b6b3c7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "nn.clusters\n",
      "  1   2   3   4   5   6   7   8   9 \n",
      " 81  90  67  57 155  51 132  38  37 \n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "library(bluster)\n",
    "#clust.5 <- clusterCells(sce.pbmc, use.dimred=\"PCA\", )\n",
    "\n",
    "\n",
    "#nn.clusters <- clusterCells(sce_vsg, use.dimred=\"UMAP\")\n",
    "nn.clusters <- clusterCells(sce_vsg, assay.type='logcounts', BLUSPARAM=NNGraphParam(k=25))\n",
    "table(nn.clusters)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d0b98d1e-dd30-4ec8-be74-c6cd2adab8d0",
   "metadata": {},
   "source": [
    "## Plot Cluster\n",
    "- here an attempt to use log counts for clustering.\n",
    "- the cluster are visualized using umap \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "d20511f9-6f9a-46a2-b51e-26048c6b89b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "colLabels(sce_vsg) <- nn.clusters\n",
    "plotReducedDim(sce_vsg, \"UMAP\", colour_by=\"label\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72d88ab2-b69a-47a1-a3e0-1384df4b358b",
   "metadata": {},
   "source": [
    "## Plot z-score\n",
    "here we compute and plot z scores for each vsgs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "1d4437e1-4337-4ba8-8abd-2902f8473164",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "R[write to console]: \n",
      "Attaching package: 'celda'\n",
      "\n",
      "\n",
      "R[write to console]: The following objects are masked from 'package:scater':\n",
      "\n",
      "    normalizeCounts, plotHeatmap\n",
      "\n",
      "\n",
      "R[write to console]: The following object is masked from 'package:scuttle':\n",
      "\n",
      "    normalizeCounts\n",
      "\n",
      "\n",
      "R[write to console]: The following object is masked from 'package:S4Vectors':\n",
      "\n",
      "    params\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R -w 800 -h 800\n",
    "library(celda)\n",
    "umap <- reducedDim(sce_vsg, \"UMAP\")\n",
    "plotDimReduceFeature(as.matrix(logcounts(sce_vsg)),\n",
    "    dim1 = umap[, 1],\n",
    "    dim2 = umap[, 2],\n",
    "    features = rownames(sce_vsg),#c('vsg-2-Tb427.BES40.22', 'vsg-6-Tb427.BES15.12'),\n",
    "    exactMatch = TRUE)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2889512c-63ff-4b4f-99f6-fb6a6f34a94a",
   "metadata": {},
   "source": [
    "## Plot log counts\n",
    "here we plot the log counts of the vsgs withput scaling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "d309f1c0-d03e-4a85-b6d0-7a29cf73f5c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R -w 800 -h 800\n",
    "library(celda)\n",
    "umap <- reducedDim(sce_vsg, \"UMAP\")\n",
    "plotDimReduceFeature(as.matrix(logcounts(sce_vsg)),\n",
    "    dim1 = umap[, 1],\n",
    "    dim2 = umap[, 2],\n",
    "    features = rownames(sce_vsg),#c('vsg-2-Tb427.BES40.22', 'vsg-6-Tb427.BES15.12'),\n",
    "    exactMatch = TRUE,\n",
    "    zscore=FALSE,\n",
    "    trim = c(0, 10),                 \n",
    "    limits = c(0, 10),)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "7d4269db-e791-46aa-95bd-2a0e9c475850",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] 14.75694\n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "max(logcounts(sce_vsg))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "b1fde65f-5c75-48fc-bf75-3f130dd84206",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] 4 3 7 5 7 6\n",
      "Levels: 1 2 3 4 5 6 7 8 9\n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "head(colLabels(sce_vsg))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "8774953d-82c8-4969-9846-55a9fc278431",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%R\n",
    "rd<-reducedDim(sce_vsg, \"UMAP\")[,1:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "0288a1ef-a42c-45f4-9050-bbf53a339f8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "%R -o rd\n",
    "umap = pd.DataFrame(rd)\n",
    "umap.columns = ['comp1','comp2']\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "b59048b0-b634-48b9-87b6-ea673dde0d1c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] 4 3 7 5 7 6\n",
      "Levels: 1 2 3 4 5 6 7 8 9\n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "lab<-colLabels(sce_vsg)\n",
    "head(lab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "14fa9f65-5488-4800-8f1c-43d0bff8d42b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vsg-2-Tb427.BES40.22</th>\n",
       "      <th>vsg-9-Tb427.BES129.14</th>\n",
       "      <th>vsg-6-Tb427.BES15.12</th>\n",
       "      <th>vsg-21-Tb427.BES28.15</th>\n",
       "      <th>vsg-18-Tb427.BES98.12</th>\n",
       "      <th>vsg-3-Tb427.BES65.13</th>\n",
       "      <th>vsg-14-Tb427.BES64.2</th>\n",
       "      <th>vsg-15-Tb427.BES134.6</th>\n",
       "      <th>vsg-16-Tb427.BES122.11</th>\n",
       "      <th>vsg-8-Tb427.BES29.9</th>\n",
       "      <th>...</th>\n",
       "      <th>vsg-mes-Tb427VSG-531</th>\n",
       "      <th>vsg-mes-Tb427VSG-639</th>\n",
       "      <th>vsg-mes-Tb427VSG-653</th>\n",
       "      <th>vsg-mes-Tb427VSG-1954</th>\n",
       "      <th>vsg-mes-Tb427VSG-636</th>\n",
       "      <th>vsg-mes-Tb427VSG-559</th>\n",
       "      <th>vsg-mes-Tb427VSG-3591</th>\n",
       "      <th>comp1</th>\n",
       "      <th>comp2</th>\n",
       "      <th>clusters</th>\n",
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       "    <tr>\n",
       "      <th>index</th>\n",
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       "      <th></th>\n",
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       "      <td>2.499921</td>\n",
       "      <td>4</td>\n",
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       "      <th>AAACCCATCTTCTGTA-1</th>\n",
       "      <td>7.092507</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.889263</td>\n",
       "      <td>-6.209695</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACGAACATAGGTAA-1</th>\n",
       "      <td>4.543672</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.894194</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.442090</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-7.084458</td>\n",
       "      <td>5.145591</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACGAAGTACAGTAA-1</th>\n",
       "      <td>7.562260</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.429597</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-3.775119</td>\n",
       "      <td>1.836348</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAAGAACCATGAGAAT-1</th>\n",
       "      <td>4.822199</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.857582</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-6.715941</td>\n",
       "      <td>4.457271</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    vsg-2-Tb427.BES40.22  vsg-9-Tb427.BES129.14  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1              9.387856                    0.0   \n",
       "AAACCCATCTTCTGTA-1              7.092507                    0.0   \n",
       "AAACGAACATAGGTAA-1              4.543672                    0.0   \n",
       "AAACGAAGTACAGTAA-1              7.562260                    0.0   \n",
       "AAAGAACCATGAGAAT-1              4.822199                    0.0   \n",
       "\n",
       "                    vsg-6-Tb427.BES15.12  vsg-21-Tb427.BES28.15  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                   0.0                    0.0   \n",
       "AAACCCATCTTCTGTA-1                   0.0                    0.0   \n",
       "AAACGAACATAGGTAA-1                   0.0                    0.0   \n",
       "AAACGAAGTACAGTAA-1                   0.0                    0.0   \n",
       "AAAGAACCATGAGAAT-1                   0.0                    0.0   \n",
       "\n",
       "                    vsg-18-Tb427.BES98.12  vsg-3-Tb427.BES65.13  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                    0.0                   0.0   \n",
       "AAACCCATCTTCTGTA-1                    0.0                   0.0   \n",
       "AAACGAACATAGGTAA-1                    0.0                   0.0   \n",
       "AAACGAAGTACAGTAA-1                    0.0                   0.0   \n",
       "AAAGAACCATGAGAAT-1                    0.0                   0.0   \n",
       "\n",
       "                    vsg-14-Tb427.BES64.2  vsg-15-Tb427.BES134.6  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                   0.0               0.000000   \n",
       "AAACCCATCTTCTGTA-1                   0.0               0.000000   \n",
       "AAACGAACATAGGTAA-1                   0.0               0.894194   \n",
       "AAACGAAGTACAGTAA-1                   0.0               0.000000   \n",
       "AAAGAACCATGAGAAT-1                   0.0               0.000000   \n",
       "\n",
       "                    vsg-16-Tb427.BES122.11  vsg-8-Tb427.BES29.9  ...  \\\n",
       "index                                                            ...   \n",
       "AAACCCACAATAGTGA-1                     0.0             0.000000  ...   \n",
       "AAACCCATCTTCTGTA-1                     0.0             0.000000  ...   \n",
       "AAACGAACATAGGTAA-1                     0.0             1.442090  ...   \n",
       "AAACGAAGTACAGTAA-1                     0.0             1.429597  ...   \n",
       "AAAGAACCATGAGAAT-1                     0.0             1.857582  ...   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-531  vsg-mes-Tb427VSG-639  \\\n",
       "index                                                            \n",
       "AAACCCACAATAGTGA-1                   0.0                   0.0   \n",
       "AAACCCATCTTCTGTA-1                   0.0                   0.0   \n",
       "AAACGAACATAGGTAA-1                   0.0                   0.0   \n",
       "AAACGAAGTACAGTAA-1                   0.0                   0.0   \n",
       "AAAGAACCATGAGAAT-1                   0.0                   0.0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-653  vsg-mes-Tb427VSG-1954  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                   0.0                    0.0   \n",
       "AAACCCATCTTCTGTA-1                   0.0                    0.0   \n",
       "AAACGAACATAGGTAA-1                   0.0                    0.0   \n",
       "AAACGAAGTACAGTAA-1                   0.0                    0.0   \n",
       "AAAGAACCATGAGAAT-1                   0.0                    0.0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-636  vsg-mes-Tb427VSG-559  \\\n",
       "index                                                            \n",
       "AAACCCACAATAGTGA-1                   0.0                   0.0   \n",
       "AAACCCATCTTCTGTA-1                   0.0                   0.0   \n",
       "AAACGAACATAGGTAA-1                   0.0                   0.0   \n",
       "AAACGAAGTACAGTAA-1                   0.0                   0.0   \n",
       "AAAGAACCATGAGAAT-1                   0.0                   0.0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-3591     comp1     comp2  clusters  \n",
       "index                                                                    \n",
       "AAACCCACAATAGTGA-1                    0.0  0.066402  2.499921         4  \n",
       "AAACCCATCTTCTGTA-1                    0.0  0.889263 -6.209695         3  \n",
       "AAACGAACATAGGTAA-1                    0.0 -7.084458  5.145591         7  \n",
       "AAACGAAGTACAGTAA-1                    0.0 -3.775119  1.836348         5  \n",
       "AAAGAACCATGAGAAT-1                    0.0 -6.715941  4.457271         7  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%R -o lab\n",
    "umap = pd.concat([pd.read_csv('new_count_vsg_vex1_2_norm.csv').T.reset_index(),umap],axis=1)\n",
    "umap=umap.set_index('index')\n",
    "umap['clusters']=list(lab)\n",
    "umap.to_csv('new_count_vsg_vex1_2_norm.csv')\n",
    "umap.head()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "f1ce51a6-4944-4196-bef1-98fee3e6bcd7",
   "metadata": {},
   "outputs": [],
   "source": [
    "%R -o rd\n",
    "umap = pd.DataFrame(rd)\n",
    "umap.columns = ['comp1','comp2']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "915f9ee1-ef02-41b5-92a7-7603b0814872",
   "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>vsg-2-Tb427.BES40.22</th>\n",
       "      <th>vsg-9-Tb427.BES129.14</th>\n",
       "      <th>vsg-6-Tb427.BES15.12</th>\n",
       "      <th>vsg-21-Tb427.BES28.15</th>\n",
       "      <th>vsg-18-Tb427.BES98.12</th>\n",
       "      <th>vsg-3-Tb427.BES65.13</th>\n",
       "      <th>vsg-14-Tb427.BES64.2</th>\n",
       "      <th>vsg-15-Tb427.BES134.6</th>\n",
       "      <th>vsg-16-Tb427.BES122.11</th>\n",
       "      <th>vsg-8-Tb427.BES29.9</th>\n",
       "      <th>...</th>\n",
       "      <th>vsg-mes-Tb427VSG-531</th>\n",
       "      <th>vsg-mes-Tb427VSG-639</th>\n",
       "      <th>vsg-mes-Tb427VSG-653</th>\n",
       "      <th>vsg-mes-Tb427VSG-1954</th>\n",
       "      <th>vsg-mes-Tb427VSG-636</th>\n",
       "      <th>vsg-mes-Tb427VSG-559</th>\n",
       "      <th>vsg-mes-Tb427VSG-3591</th>\n",
       "      <th>comp1</th>\n",
       "      <th>comp2</th>\n",
       "      <th>clusters</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>index</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>AAACCCACAATAGTGA-1</th>\n",
       "      <td>49</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</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>0</td>\n",
       "      <td>0.066402</td>\n",
       "      <td>2.499921</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACCCATCTTCTGTA-1</th>\n",
       "      <td>48</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</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>0</td>\n",
       "      <td>0.889263</td>\n",
       "      <td>-6.209695</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACGAACATAGGTAA-1</th>\n",
       "      <td>52</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>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>...</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>0</td>\n",
       "      <td>-7.084458</td>\n",
       "      <td>5.145591</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACGAAGTACAGTAA-1</th>\n",
       "      <td>111</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</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>0</td>\n",
       "      <td>-3.775119</td>\n",
       "      <td>1.836348</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAAGAACCATGAGAAT-1</th>\n",
       "      <td>52</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>...</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>0</td>\n",
       "      <td>-6.715941</td>\n",
       "      <td>4.457271</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    vsg-2-Tb427.BES40.22  vsg-9-Tb427.BES129.14  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                    49                      0   \n",
       "AAACCCATCTTCTGTA-1                    48                      0   \n",
       "AAACGAACATAGGTAA-1                    52                      0   \n",
       "AAACGAAGTACAGTAA-1                   111                      0   \n",
       "AAAGAACCATGAGAAT-1                    52                      0   \n",
       "\n",
       "                    vsg-6-Tb427.BES15.12  vsg-21-Tb427.BES28.15  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                     0                      0   \n",
       "AAACCCATCTTCTGTA-1                     0                      0   \n",
       "AAACGAACATAGGTAA-1                     0                      0   \n",
       "AAACGAAGTACAGTAA-1                     0                      0   \n",
       "AAAGAACCATGAGAAT-1                     0                      0   \n",
       "\n",
       "                    vsg-18-Tb427.BES98.12  vsg-3-Tb427.BES65.13  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                      0                     0   \n",
       "AAACCCATCTTCTGTA-1                      0                     0   \n",
       "AAACGAACATAGGTAA-1                      0                     0   \n",
       "AAACGAAGTACAGTAA-1                      0                     0   \n",
       "AAAGAACCATGAGAAT-1                      0                     0   \n",
       "\n",
       "                    vsg-14-Tb427.BES64.2  vsg-15-Tb427.BES134.6  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                     0                      0   \n",
       "AAACCCATCTTCTGTA-1                     0                      0   \n",
       "AAACGAACATAGGTAA-1                     0                      2   \n",
       "AAACGAAGTACAGTAA-1                     0                      0   \n",
       "AAAGAACCATGAGAAT-1                     0                      0   \n",
       "\n",
       "                    vsg-16-Tb427.BES122.11  vsg-8-Tb427.BES29.9  ...  \\\n",
       "index                                                            ...   \n",
       "AAACCCACAATAGTGA-1                       0                    0  ...   \n",
       "AAACCCATCTTCTGTA-1                       0                    0  ...   \n",
       "AAACGAACATAGGTAA-1                       0                    4  ...   \n",
       "AAACGAAGTACAGTAA-1                       0                    1  ...   \n",
       "AAAGAACCATGAGAAT-1                       0                    5  ...   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-531  vsg-mes-Tb427VSG-639  \\\n",
       "index                                                            \n",
       "AAACCCACAATAGTGA-1                     0                     0   \n",
       "AAACCCATCTTCTGTA-1                     0                     0   \n",
       "AAACGAACATAGGTAA-1                     0                     0   \n",
       "AAACGAAGTACAGTAA-1                     0                     0   \n",
       "AAAGAACCATGAGAAT-1                     0                     0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-653  vsg-mes-Tb427VSG-1954  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                     0                      0   \n",
       "AAACCCATCTTCTGTA-1                     0                      0   \n",
       "AAACGAACATAGGTAA-1                     0                      0   \n",
       "AAACGAAGTACAGTAA-1                     0                      0   \n",
       "AAAGAACCATGAGAAT-1                     0                      0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-636  vsg-mes-Tb427VSG-559  \\\n",
       "index                                                            \n",
       "AAACCCACAATAGTGA-1                     0                     0   \n",
       "AAACCCATCTTCTGTA-1                     0                     0   \n",
       "AAACGAACATAGGTAA-1                     0                     0   \n",
       "AAACGAAGTACAGTAA-1                     0                     0   \n",
       "AAAGAACCATGAGAAT-1                     0                     0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-3591     comp1     comp2  clusters  \n",
       "index                                                                    \n",
       "AAACCCACAATAGTGA-1                      0  0.066402  2.499921         4  \n",
       "AAACCCATCTTCTGTA-1                      0  0.889263 -6.209695         3  \n",
       "AAACGAACATAGGTAA-1                      0 -7.084458  5.145591         7  \n",
       "AAACGAAGTACAGTAA-1                      0 -3.775119  1.836348         5  \n",
       "AAAGAACCATGAGAAT-1                      0 -6.715941  4.457271         7  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%R -o lab\n",
    "umap = pd.concat([pd.read_csv(\"new_count_vsg_vex1_2.csv\").T.reset_index(),umap],axis=1)\n",
    "umap=umap.set_index('index')\n",
    "umap['clusters']=list(lab)\n",
    "umap.to_csv(\"new_count_vsg_vex1_2.csv\")\n",
    "umap.head()\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "5c78ee0e-e96f-49b9-9b07-9567327c825f",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%R\n",
    "count_feature <- colSums(counts(sce_vsg)>0)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0a77cb9-6836-4609-a2d8-de3e316932b8",
   "metadata": {},
   "source": [
    "## Plot umap vsg size\n",
    "The umap is color coded by the number ov vsgs expressed in each cell\n",
    "The center yellow blob show the cell expressin all 5 vsgs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "c948cef5-7dce-4b01-9262-bc183d400323",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "colLabels(sce_vsg) <- count_feature\n",
    "plotReducedDim(sce_vsg, \"UMAP\", colour_by=\"label\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "6aec4e2d-45f5-49d6-bda4-6d75ca0bf323",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vsg-2-Tb427.BES40.22</th>\n",
       "      <th>vsg-9-Tb427.BES129.14</th>\n",
       "      <th>vsg-6-Tb427.BES15.12</th>\n",
       "      <th>vsg-21-Tb427.BES28.15</th>\n",
       "      <th>vsg-18-Tb427.BES98.12</th>\n",
       "      <th>vsg-3-Tb427.BES65.13</th>\n",
       "      <th>vsg-14-Tb427.BES64.2</th>\n",
       "      <th>vsg-15-Tb427.BES134.6</th>\n",
       "      <th>vsg-16-Tb427.BES122.11</th>\n",
       "      <th>vsg-8-Tb427.BES29.9</th>\n",
       "      <th>...</th>\n",
       "      <th>vsg-mes-Tb427VSG-531</th>\n",
       "      <th>vsg-mes-Tb427VSG-639</th>\n",
       "      <th>vsg-mes-Tb427VSG-653</th>\n",
       "      <th>vsg-mes-Tb427VSG-1954</th>\n",
       "      <th>vsg-mes-Tb427VSG-636</th>\n",
       "      <th>vsg-mes-Tb427VSG-559</th>\n",
       "      <th>vsg-mes-Tb427VSG-3591</th>\n",
       "      <th>comp1</th>\n",
       "      <th>comp2</th>\n",
       "      <th>clusters</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>index</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAACCCACAATAGTGA-1</th>\n",
       "      <td>49</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>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.066402</td>\n",
       "      <td>2.499921</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACCCATCTTCTGTA-1</th>\n",
       "      <td>48</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</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>0</td>\n",
       "      <td>0.889263</td>\n",
       "      <td>-6.209695</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACGAACATAGGTAA-1</th>\n",
       "      <td>52</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>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>...</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>0</td>\n",
       "      <td>-7.084458</td>\n",
       "      <td>5.145591</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACGAAGTACAGTAA-1</th>\n",
       "      <td>111</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</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>0</td>\n",
       "      <td>-3.775119</td>\n",
       "      <td>1.836348</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAAGAACCATGAGAAT-1</th>\n",
       "      <td>52</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>...</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>0</td>\n",
       "      <td>-6.715941</td>\n",
       "      <td>4.457271</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    vsg-2-Tb427.BES40.22  vsg-9-Tb427.BES129.14  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                    49                      0   \n",
       "AAACCCATCTTCTGTA-1                    48                      0   \n",
       "AAACGAACATAGGTAA-1                    52                      0   \n",
       "AAACGAAGTACAGTAA-1                   111                      0   \n",
       "AAAGAACCATGAGAAT-1                    52                      0   \n",
       "\n",
       "                    vsg-6-Tb427.BES15.12  vsg-21-Tb427.BES28.15  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                     0                      0   \n",
       "AAACCCATCTTCTGTA-1                     0                      0   \n",
       "AAACGAACATAGGTAA-1                     0                      0   \n",
       "AAACGAAGTACAGTAA-1                     0                      0   \n",
       "AAAGAACCATGAGAAT-1                     0                      0   \n",
       "\n",
       "                    vsg-18-Tb427.BES98.12  vsg-3-Tb427.BES65.13  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                      0                     0   \n",
       "AAACCCATCTTCTGTA-1                      0                     0   \n",
       "AAACGAACATAGGTAA-1                      0                     0   \n",
       "AAACGAAGTACAGTAA-1                      0                     0   \n",
       "AAAGAACCATGAGAAT-1                      0                     0   \n",
       "\n",
       "                    vsg-14-Tb427.BES64.2  vsg-15-Tb427.BES134.6  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                     0                      0   \n",
       "AAACCCATCTTCTGTA-1                     0                      0   \n",
       "AAACGAACATAGGTAA-1                     0                      2   \n",
       "AAACGAAGTACAGTAA-1                     0                      0   \n",
       "AAAGAACCATGAGAAT-1                     0                      0   \n",
       "\n",
       "                    vsg-16-Tb427.BES122.11  vsg-8-Tb427.BES29.9  ...  \\\n",
       "index                                                            ...   \n",
       "AAACCCACAATAGTGA-1                       0                    0  ...   \n",
       "AAACCCATCTTCTGTA-1                       0                    0  ...   \n",
       "AAACGAACATAGGTAA-1                       0                    4  ...   \n",
       "AAACGAAGTACAGTAA-1                       0                    1  ...   \n",
       "AAAGAACCATGAGAAT-1                       0                    5  ...   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-531  vsg-mes-Tb427VSG-639  \\\n",
       "index                                                            \n",
       "AAACCCACAATAGTGA-1                     0                     0   \n",
       "AAACCCATCTTCTGTA-1                     0                     0   \n",
       "AAACGAACATAGGTAA-1                     0                     0   \n",
       "AAACGAAGTACAGTAA-1                     0                     0   \n",
       "AAAGAACCATGAGAAT-1                     0                     0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-653  vsg-mes-Tb427VSG-1954  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                     0                      0   \n",
       "AAACCCATCTTCTGTA-1                     0                      0   \n",
       "AAACGAACATAGGTAA-1                     0                      0   \n",
       "AAACGAAGTACAGTAA-1                     0                      0   \n",
       "AAAGAACCATGAGAAT-1                     0                      0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-636  vsg-mes-Tb427VSG-559  \\\n",
       "index                                                            \n",
       "AAACCCACAATAGTGA-1                     0                     0   \n",
       "AAACCCATCTTCTGTA-1                     0                     0   \n",
       "AAACGAACATAGGTAA-1                     0                     0   \n",
       "AAACGAAGTACAGTAA-1                     0                     0   \n",
       "AAAGAACCATGAGAAT-1                     0                     0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-3591     comp1     comp2  clusters  \n",
       "index                                                                    \n",
       "AAACCCACAATAGTGA-1                      0  0.066402  2.499921         4  \n",
       "AAACCCATCTTCTGTA-1                      0  0.889263 -6.209695         3  \n",
       "AAACGAACATAGGTAA-1                      0 -7.084458  5.145591         7  \n",
       "AAACGAAGTACAGTAA-1                      0 -3.775119  1.836348         5  \n",
       "AAAGAACCATGAGAAT-1                      0 -6.715941  4.457271         7  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#%%R\n",
    "#is.vsg6_8 <- is.vsg6 | is.vsg8 \n",
    "#is.other <- is.vsg15 | is.vsg17 | is.vsg2\n",
    "#is.vsg6_8 <- is.vsg6_8 & is.other \n",
    "umap.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "89ff0332-5725-4e08-97f4-5c1e8d6af44f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "vsg-16-Tb427.BES122.11        0\n",
       "vsg-9-Tb427.BES129.14         0\n",
       "vsg-21-Tb427.BES28.15         0\n",
       "vsg-19-Tb427.BES10.10         0\n",
       "vsg-mes-Tb427VSG-559          0\n",
       "vsg-mes-Tb427VSG-639          0\n",
       "vsg-13-Tb427.BES51.12         3\n",
       "vsg-18-Tb427.BES98.12         3\n",
       "vsg-mes-Tb427VSG-653          7\n",
       "vsg-mes-Tb427VSG-1954        14\n",
       "vsg-mes-Tb427VSG-3591        19\n",
       "vsg-mes-Tb427VSG-636         26\n",
       "vsg-14-Tb427.BES64.2         43\n",
       "vsg-11-Tb427.BES126.15       51\n",
       "vsg-3-Tb427.BES65.13         58\n",
       "vsg-mes-Tb427VSG-531         66\n",
       "vsg-mes-Tb427VSG-397         67\n",
       "vsg-15-Tb427.BES134.6        77\n",
       "vsg-17-Tb427.BES56.13       115\n",
       "vsg-6-Tb427.BES15.12        204\n",
       "vsg-8-Tb427.BES29.9         575\n",
       "vsg-2-Tb427.BES40.22      44351\n",
       "dtype: object"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "umap.sum().drop(['comp1','comp2','clusters']).sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "41a3f3f6-563c-463b-8963-35f473d01140",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9eb77e60-e6ca-4888-a51c-9d40072aed85",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bfb56412-e0c9-4f53-b1fc-896e57459e21",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d4935ef-e798-4d5f-b42a-d264aeef8016",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "06376f0e-b018-4dcd-99ff-a4bd601bde40",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vsg-2-Tb427.BES40.22</th>\n",
       "      <th>vsg-9-Tb427.BES129.14</th>\n",
       "      <th>vsg-6-Tb427.BES15.12</th>\n",
       "      <th>vsg-21-Tb427.BES28.15</th>\n",
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       "      <th>vsg-3-Tb427.BES65.13</th>\n",
       "      <th>vsg-14-Tb427.BES64.2</th>\n",
       "      <th>vsg-15-Tb427.BES134.6</th>\n",
       "      <th>vsg-16-Tb427.BES122.11</th>\n",
       "      <th>vsg-8-Tb427.BES29.9</th>\n",
       "      <th>...</th>\n",
       "      <th>vsg-11-Tb427.BES126.15</th>\n",
       "      <th>vsg-13-Tb427.BES51.12</th>\n",
       "      <th>vsg-mes-Tb427VSG-397</th>\n",
       "      <th>vsg-mes-Tb427VSG-531</th>\n",
       "      <th>vsg-mes-Tb427VSG-639</th>\n",
       "      <th>vsg-mes-Tb427VSG-653</th>\n",
       "      <th>vsg-mes-Tb427VSG-1954</th>\n",
       "      <th>vsg-mes-Tb427VSG-636</th>\n",
       "      <th>vsg-mes-Tb427VSG-559</th>\n",
       "      <th>vsg-mes-Tb427VSG-3591</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>index</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>AAACCCACAATAGTGA-1</th>\n",
       "      <td>49</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACCCATCTTCTGTA-1</th>\n",
       "      <td>48</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACGAACATAGGTAA-1</th>\n",
       "      <td>52</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>2</td>\n",
       "      <td>0</td>\n",
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       "      <td>...</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACGAAGTACAGTAA-1</th>\n",
       "      <td>111</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAAGAACCATGAGAAT-1</th>\n",
       "      <td>52</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>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <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>0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
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      ],
      "text/plain": [
       "                    vsg-2-Tb427.BES40.22  vsg-9-Tb427.BES129.14  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                    49                      0   \n",
       "AAACCCATCTTCTGTA-1                    48                      0   \n",
       "AAACGAACATAGGTAA-1                    52                      0   \n",
       "AAACGAAGTACAGTAA-1                   111                      0   \n",
       "AAAGAACCATGAGAAT-1                    52                      0   \n",
       "\n",
       "                    vsg-6-Tb427.BES15.12  vsg-21-Tb427.BES28.15  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                     0                      0   \n",
       "AAACCCATCTTCTGTA-1                     0                      0   \n",
       "AAACGAACATAGGTAA-1                     0                      0   \n",
       "AAACGAAGTACAGTAA-1                     0                      0   \n",
       "AAAGAACCATGAGAAT-1                     0                      0   \n",
       "\n",
       "                    vsg-18-Tb427.BES98.12  vsg-3-Tb427.BES65.13  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                      0                     0   \n",
       "AAACCCATCTTCTGTA-1                      0                     0   \n",
       "AAACGAACATAGGTAA-1                      0                     0   \n",
       "AAACGAAGTACAGTAA-1                      0                     0   \n",
       "AAAGAACCATGAGAAT-1                      0                     0   \n",
       "\n",
       "                    vsg-14-Tb427.BES64.2  vsg-15-Tb427.BES134.6  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                     0                      0   \n",
       "AAACCCATCTTCTGTA-1                     0                      0   \n",
       "AAACGAACATAGGTAA-1                     0                      2   \n",
       "AAACGAAGTACAGTAA-1                     0                      0   \n",
       "AAAGAACCATGAGAAT-1                     0                      0   \n",
       "\n",
       "                    vsg-16-Tb427.BES122.11  vsg-8-Tb427.BES29.9  ...  \\\n",
       "index                                                            ...   \n",
       "AAACCCACAATAGTGA-1                       0                    0  ...   \n",
       "AAACCCATCTTCTGTA-1                       0                    0  ...   \n",
       "AAACGAACATAGGTAA-1                       0                    4  ...   \n",
       "AAACGAAGTACAGTAA-1                       0                    1  ...   \n",
       "AAAGAACCATGAGAAT-1                       0                    5  ...   \n",
       "\n",
       "                    vsg-11-Tb427.BES126.15  vsg-13-Tb427.BES51.12  \\\n",
       "index                                                               \n",
       "AAACCCACAATAGTGA-1                       0                      0   \n",
       "AAACCCATCTTCTGTA-1                       0                      0   \n",
       "AAACGAACATAGGTAA-1                       0                      0   \n",
       "AAACGAAGTACAGTAA-1                       0                      0   \n",
       "AAAGAACCATGAGAAT-1                       0                      0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-397  vsg-mes-Tb427VSG-531  \\\n",
       "index                                                            \n",
       "AAACCCACAATAGTGA-1                     0                     0   \n",
       "AAACCCATCTTCTGTA-1                     0                     0   \n",
       "AAACGAACATAGGTAA-1                     0                     0   \n",
       "AAACGAAGTACAGTAA-1                     0                     0   \n",
       "AAAGAACCATGAGAAT-1                     0                     0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-639  vsg-mes-Tb427VSG-653  \\\n",
       "index                                                            \n",
       "AAACCCACAATAGTGA-1                     0                     0   \n",
       "AAACCCATCTTCTGTA-1                     0                     0   \n",
       "AAACGAACATAGGTAA-1                     0                     0   \n",
       "AAACGAAGTACAGTAA-1                     0                     0   \n",
       "AAAGAACCATGAGAAT-1                     0                     0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-1954  vsg-mes-Tb427VSG-636  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                      0                     0   \n",
       "AAACCCATCTTCTGTA-1                      0                     0   \n",
       "AAACGAACATAGGTAA-1                      0                     0   \n",
       "AAACGAAGTACAGTAA-1                      0                     0   \n",
       "AAAGAACCATGAGAAT-1                      0                     0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-559  vsg-mes-Tb427VSG-3591  \n",
       "index                                                            \n",
       "AAACCCACAATAGTGA-1                     0                      0  \n",
       "AAACCCATCTTCTGTA-1                     0                      0  \n",
       "AAACGAACATAGGTAA-1                     0                      0  \n",
       "AAACGAAGTACAGTAA-1                     0                      0  \n",
       "AAAGAACCATGAGAAT-1                     0                      0  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "select = umap.drop(['comp1','comp2','clusters'],axis=1)\n",
    "select.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "fd935164-53f9-4c50-b03c-720cdb6fe3ca",
   "metadata": {},
   "outputs": [
    {
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       "      <th>vsg-2-Tb427.BES40.22</th>\n",
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       "      <th>vsg-mes-Tb427VSG-3591</th>\n",
       "      <th>comp1</th>\n",
       "      <th>comp2</th>\n",
       "      <th>clusters</th>\n",
       "      <th>vsg_class</th>\n",
       "      <th>size_class</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>index</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>AAACCCACAATAGTGA-1</th>\n",
       "      <td>49</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.066402</td>\n",
       "      <td>2.499921</td>\n",
       "      <td>4</td>\n",
       "      <td>(vsg-17-Tb427.BES56.13, vsg-2-Tb427.BES40.22)</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACCCATCTTCTGTA-1</th>\n",
       "      <td>48</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.889263</td>\n",
       "      <td>-6.209695</td>\n",
       "      <td>3</td>\n",
       "      <td>(vsg-2-Tb427.BES40.22,)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACGAACATAGGTAA-1</th>\n",
       "      <td>52</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>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-7.084458</td>\n",
       "      <td>5.145591</td>\n",
       "      <td>7</td>\n",
       "      <td>(vsg-15-Tb427.BES134.6, vsg-2-Tb427.BES40.22, ...</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACGAAGTACAGTAA-1</th>\n",
       "      <td>111</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-3.775119</td>\n",
       "      <td>1.836348</td>\n",
       "      <td>5</td>\n",
       "      <td>(vsg-2-Tb427.BES40.22, vsg-8-Tb427.BES29.9)</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAAGAACCATGAGAAT-1</th>\n",
       "      <td>52</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-6.715941</td>\n",
       "      <td>4.457271</td>\n",
       "      <td>7</td>\n",
       "      <td>(vsg-2-Tb427.BES40.22, vsg-8-Tb427.BES29.9)</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    vsg-2-Tb427.BES40.22  vsg-9-Tb427.BES129.14  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                    49                      0   \n",
       "AAACCCATCTTCTGTA-1                    48                      0   \n",
       "AAACGAACATAGGTAA-1                    52                      0   \n",
       "AAACGAAGTACAGTAA-1                   111                      0   \n",
       "AAAGAACCATGAGAAT-1                    52                      0   \n",
       "\n",
       "                    vsg-6-Tb427.BES15.12  vsg-21-Tb427.BES28.15  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                     0                      0   \n",
       "AAACCCATCTTCTGTA-1                     0                      0   \n",
       "AAACGAACATAGGTAA-1                     0                      0   \n",
       "AAACGAAGTACAGTAA-1                     0                      0   \n",
       "AAAGAACCATGAGAAT-1                     0                      0   \n",
       "\n",
       "                    vsg-18-Tb427.BES98.12  vsg-3-Tb427.BES65.13  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                      0                     0   \n",
       "AAACCCATCTTCTGTA-1                      0                     0   \n",
       "AAACGAACATAGGTAA-1                      0                     0   \n",
       "AAACGAAGTACAGTAA-1                      0                     0   \n",
       "AAAGAACCATGAGAAT-1                      0                     0   \n",
       "\n",
       "                    vsg-14-Tb427.BES64.2  vsg-15-Tb427.BES134.6  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                     0                      0   \n",
       "AAACCCATCTTCTGTA-1                     0                      0   \n",
       "AAACGAACATAGGTAA-1                     0                      2   \n",
       "AAACGAAGTACAGTAA-1                     0                      0   \n",
       "AAAGAACCATGAGAAT-1                     0                      0   \n",
       "\n",
       "                    vsg-16-Tb427.BES122.11  vsg-8-Tb427.BES29.9  ...  \\\n",
       "index                                                            ...   \n",
       "AAACCCACAATAGTGA-1                       0                    0  ...   \n",
       "AAACCCATCTTCTGTA-1                       0                    0  ...   \n",
       "AAACGAACATAGGTAA-1                       0                    4  ...   \n",
       "AAACGAAGTACAGTAA-1                       0                    1  ...   \n",
       "AAAGAACCATGAGAAT-1                       0                    5  ...   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-653  vsg-mes-Tb427VSG-1954  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                     0                      0   \n",
       "AAACCCATCTTCTGTA-1                     0                      0   \n",
       "AAACGAACATAGGTAA-1                     0                      0   \n",
       "AAACGAAGTACAGTAA-1                     0                      0   \n",
       "AAAGAACCATGAGAAT-1                     0                      0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-636  vsg-mes-Tb427VSG-559  \\\n",
       "index                                                            \n",
       "AAACCCACAATAGTGA-1                     0                     0   \n",
       "AAACCCATCTTCTGTA-1                     0                     0   \n",
       "AAACGAACATAGGTAA-1                     0                     0   \n",
       "AAACGAAGTACAGTAA-1                     0                     0   \n",
       "AAAGAACCATGAGAAT-1                     0                     0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-3591     comp1     comp2  clusters  \\\n",
       "index                                                                     \n",
       "AAACCCACAATAGTGA-1                      0  0.066402  2.499921         4   \n",
       "AAACCCATCTTCTGTA-1                      0  0.889263 -6.209695         3   \n",
       "AAACGAACATAGGTAA-1                      0 -7.084458  5.145591         7   \n",
       "AAACGAAGTACAGTAA-1                      0 -3.775119  1.836348         5   \n",
       "AAAGAACCATGAGAAT-1                      0 -6.715941  4.457271         7   \n",
       "\n",
       "                                                            vsg_class  \\\n",
       "index                                                                   \n",
       "AAACCCACAATAGTGA-1      (vsg-17-Tb427.BES56.13, vsg-2-Tb427.BES40.22)   \n",
       "AAACCCATCTTCTGTA-1                            (vsg-2-Tb427.BES40.22,)   \n",
       "AAACGAACATAGGTAA-1  (vsg-15-Tb427.BES134.6, vsg-2-Tb427.BES40.22, ...   \n",
       "AAACGAAGTACAGTAA-1        (vsg-2-Tb427.BES40.22, vsg-8-Tb427.BES29.9)   \n",
       "AAAGAACCATGAGAAT-1        (vsg-2-Tb427.BES40.22, vsg-8-Tb427.BES29.9)   \n",
       "\n",
       "                    size_class  \n",
       "index                           \n",
       "AAACCCACAATAGTGA-1           2  \n",
       "AAACCCATCTTCTGTA-1           1  \n",
       "AAACGAACATAGGTAA-1           3  \n",
       "AAACGAAGTACAGTAA-1           2  \n",
       "AAAGAACCATGAGAAT-1           2  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vsg_class = []\n",
    "for n in range(select.shape[0]):\n",
    "    temp = select.iloc[n]\n",
    "    temp = temp[temp>0]\n",
    "    temp = list(temp.index)\n",
    "    temp.sort()\n",
    "    #print(temp)\n",
    "    temp = [b for b in temp if b not in ['comp1','comp2']]\n",
    "    temp.sort()\n",
    "    temp=tuple(temp)\n",
    "    vsg_class.append(temp)\n",
    "    \n",
    "    \n",
    "\n",
    "umap['vsg_class'] = vsg_class\n",
    "umap['size_class'] = [len(n) for n in  umap['vsg_class']]\n",
    "umap.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "2c341fbf-5b32-4274-b0ce-e0bde5951273",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(vsg-2-Tb427.BES40.22,)                                               318\n",
       "(vsg-2-Tb427.BES40.22, vsg-8-Tb427.BES29.9)                           138\n",
       "(vsg-2-Tb427.BES40.22, vsg-6-Tb427.BES15.12)                           29\n",
       "(vsg-2-Tb427.BES40.22, vsg-3-Tb427.BES65.13)                           28\n",
       "(vsg-17-Tb427.BES56.13, vsg-2-Tb427.BES40.22)                          21\n",
       "(vsg-2-Tb427.BES40.22, vsg-6-Tb427.BES15.12, vsg-8-Tb427.BES29.9)      18\n",
       "(vsg-15-Tb427.BES134.6, vsg-2-Tb427.BES40.22, vsg-8-Tb427.BES29.9)     16\n",
       "(vsg-2-Tb427.BES40.22, vsg-mes-Tb427VSG-531)                           13\n",
       "(vsg-14-Tb427.BES64.2, vsg-2-Tb427.BES40.22)                           13\n",
       "(vsg-15-Tb427.BES134.6, vsg-2-Tb427.BES40.22)                          13\n",
       "Name: vsg_class, dtype: int64"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "umap.vsg_class.value_counts().head(10)\n",
    "#(vsg-2-Tb427.BES40.22, vsg-6-Tb427.BES15.12) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "9306ef91-116a-43b6-ba08-bd2d18aaf565",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    318\n",
       "2    267\n",
       "3     91\n",
       "4     28\n",
       "5      3\n",
       "6      1\n",
       "Name: size_class, dtype: int64"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "umap.size_class.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "8c21c746-4bf0-4efa-b777-b191829168d9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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>vsg-2-Tb427.BES40.22</th>\n",
       "      <th>vsg-9-Tb427.BES129.14</th>\n",
       "      <th>vsg-6-Tb427.BES15.12</th>\n",
       "      <th>vsg-21-Tb427.BES28.15</th>\n",
       "      <th>vsg-18-Tb427.BES98.12</th>\n",
       "      <th>vsg-3-Tb427.BES65.13</th>\n",
       "      <th>vsg-14-Tb427.BES64.2</th>\n",
       "      <th>vsg-15-Tb427.BES134.6</th>\n",
       "      <th>vsg-16-Tb427.BES122.11</th>\n",
       "      <th>vsg-8-Tb427.BES29.9</th>\n",
       "      <th>...</th>\n",
       "      <th>vsg-mes-Tb427VSG-653</th>\n",
       "      <th>vsg-mes-Tb427VSG-1954</th>\n",
       "      <th>vsg-mes-Tb427VSG-636</th>\n",
       "      <th>vsg-mes-Tb427VSG-559</th>\n",
       "      <th>vsg-mes-Tb427VSG-3591</th>\n",
       "      <th>comp1</th>\n",
       "      <th>comp2</th>\n",
       "      <th>clusters</th>\n",
       "      <th>vsg_class</th>\n",
       "      <th>size_class</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>index</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>AAACCCACAATAGTGA-1</th>\n",
       "      <td>49</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.066402</td>\n",
       "      <td>2.499921</td>\n",
       "      <td>4</td>\n",
       "      <td>(vsg-17-Tb427.BES56.13, vsg-2-Tb427.BES40.22)</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACCCATCTTCTGTA-1</th>\n",
       "      <td>48</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.889263</td>\n",
       "      <td>-6.209695</td>\n",
       "      <td>3</td>\n",
       "      <td>(vsg-2-Tb427.BES40.22,)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACGAACATAGGTAA-1</th>\n",
       "      <td>52</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>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-7.084458</td>\n",
       "      <td>5.145591</td>\n",
       "      <td>7</td>\n",
       "      <td>(vsg-15-Tb427.BES134.6, vsg-2-Tb427.BES40.22, ...</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACGAAGTACAGTAA-1</th>\n",
       "      <td>111</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-3.775119</td>\n",
       "      <td>1.836348</td>\n",
       "      <td>5</td>\n",
       "      <td>(vsg-2-Tb427.BES40.22, vsg-8-Tb427.BES29.9)</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAAGAACCATGAGAAT-1</th>\n",
       "      <td>52</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-6.715941</td>\n",
       "      <td>4.457271</td>\n",
       "      <td>7</td>\n",
       "      <td>(vsg-2-Tb427.BES40.22, vsg-8-Tb427.BES29.9)</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    vsg-2-Tb427.BES40.22  vsg-9-Tb427.BES129.14  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                    49                      0   \n",
       "AAACCCATCTTCTGTA-1                    48                      0   \n",
       "AAACGAACATAGGTAA-1                    52                      0   \n",
       "AAACGAAGTACAGTAA-1                   111                      0   \n",
       "AAAGAACCATGAGAAT-1                    52                      0   \n",
       "\n",
       "                    vsg-6-Tb427.BES15.12  vsg-21-Tb427.BES28.15  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                     0                      0   \n",
       "AAACCCATCTTCTGTA-1                     0                      0   \n",
       "AAACGAACATAGGTAA-1                     0                      0   \n",
       "AAACGAAGTACAGTAA-1                     0                      0   \n",
       "AAAGAACCATGAGAAT-1                     0                      0   \n",
       "\n",
       "                    vsg-18-Tb427.BES98.12  vsg-3-Tb427.BES65.13  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                      0                     0   \n",
       "AAACCCATCTTCTGTA-1                      0                     0   \n",
       "AAACGAACATAGGTAA-1                      0                     0   \n",
       "AAACGAAGTACAGTAA-1                      0                     0   \n",
       "AAAGAACCATGAGAAT-1                      0                     0   \n",
       "\n",
       "                    vsg-14-Tb427.BES64.2  vsg-15-Tb427.BES134.6  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                     0                      0   \n",
       "AAACCCATCTTCTGTA-1                     0                      0   \n",
       "AAACGAACATAGGTAA-1                     0                      2   \n",
       "AAACGAAGTACAGTAA-1                     0                      0   \n",
       "AAAGAACCATGAGAAT-1                     0                      0   \n",
       "\n",
       "                    vsg-16-Tb427.BES122.11  vsg-8-Tb427.BES29.9  ...  \\\n",
       "index                                                            ...   \n",
       "AAACCCACAATAGTGA-1                       0                    0  ...   \n",
       "AAACCCATCTTCTGTA-1                       0                    0  ...   \n",
       "AAACGAACATAGGTAA-1                       0                    4  ...   \n",
       "AAACGAAGTACAGTAA-1                       0                    1  ...   \n",
       "AAAGAACCATGAGAAT-1                       0                    5  ...   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-653  vsg-mes-Tb427VSG-1954  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                     0                      0   \n",
       "AAACCCATCTTCTGTA-1                     0                      0   \n",
       "AAACGAACATAGGTAA-1                     0                      0   \n",
       "AAACGAAGTACAGTAA-1                     0                      0   \n",
       "AAAGAACCATGAGAAT-1                     0                      0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-636  vsg-mes-Tb427VSG-559  \\\n",
       "index                                                            \n",
       "AAACCCACAATAGTGA-1                     0                     0   \n",
       "AAACCCATCTTCTGTA-1                     0                     0   \n",
       "AAACGAACATAGGTAA-1                     0                     0   \n",
       "AAACGAAGTACAGTAA-1                     0                     0   \n",
       "AAAGAACCATGAGAAT-1                     0                     0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-3591     comp1     comp2  clusters  \\\n",
       "index                                                                     \n",
       "AAACCCACAATAGTGA-1                      0  0.066402  2.499921         4   \n",
       "AAACCCATCTTCTGTA-1                      0  0.889263 -6.209695         3   \n",
       "AAACGAACATAGGTAA-1                      0 -7.084458  5.145591         7   \n",
       "AAACGAAGTACAGTAA-1                      0 -3.775119  1.836348         5   \n",
       "AAAGAACCATGAGAAT-1                      0 -6.715941  4.457271         7   \n",
       "\n",
       "                                                            vsg_class  \\\n",
       "index                                                                   \n",
       "AAACCCACAATAGTGA-1      (vsg-17-Tb427.BES56.13, vsg-2-Tb427.BES40.22)   \n",
       "AAACCCATCTTCTGTA-1                            (vsg-2-Tb427.BES40.22,)   \n",
       "AAACGAACATAGGTAA-1  (vsg-15-Tb427.BES134.6, vsg-2-Tb427.BES40.22, ...   \n",
       "AAACGAAGTACAGTAA-1        (vsg-2-Tb427.BES40.22, vsg-8-Tb427.BES29.9)   \n",
       "AAAGAACCATGAGAAT-1        (vsg-2-Tb427.BES40.22, vsg-8-Tb427.BES29.9)   \n",
       "\n",
       "                    size_class  \n",
       "index                           \n",
       "AAACCCACAATAGTGA-1           2  \n",
       "AAACCCATCTTCTGTA-1           1  \n",
       "AAACGAACATAGGTAA-1           3  \n",
       "AAACGAAGTACAGTAA-1           2  \n",
       "AAAGAACCATGAGAAT-1           2  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "umap.to_csv(\"new_count_vsg_vex1_2.csv\")\n",
    "umap.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "6fab977d-fb80-4dc7-b237-469320e4adad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "    }\n",
       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vsg-2-Tb427.BES40.22</th>\n",
       "      <th>vsg-9-Tb427.BES129.14</th>\n",
       "      <th>vsg-6-Tb427.BES15.12</th>\n",
       "      <th>vsg-21-Tb427.BES28.15</th>\n",
       "      <th>vsg-18-Tb427.BES98.12</th>\n",
       "      <th>vsg-3-Tb427.BES65.13</th>\n",
       "      <th>vsg-14-Tb427.BES64.2</th>\n",
       "      <th>vsg-15-Tb427.BES134.6</th>\n",
       "      <th>vsg-16-Tb427.BES122.11</th>\n",
       "      <th>vsg-8-Tb427.BES29.9</th>\n",
       "      <th>...</th>\n",
       "      <th>vsg-mes-Tb427VSG-653</th>\n",
       "      <th>vsg-mes-Tb427VSG-1954</th>\n",
       "      <th>vsg-mes-Tb427VSG-636</th>\n",
       "      <th>vsg-mes-Tb427VSG-559</th>\n",
       "      <th>vsg-mes-Tb427VSG-3591</th>\n",
       "      <th>comp1</th>\n",
       "      <th>comp2</th>\n",
       "      <th>clusters</th>\n",
       "      <th>vsg_class</th>\n",
       "      <th>size_class</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>index</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>AAACCCACAATAGTGA-1</th>\n",
       "      <td>49</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.066402</td>\n",
       "      <td>2.499921</td>\n",
       "      <td>4</td>\n",
       "      <td>('vsg-17-Tb427.BES56.13', 'vsg-2-Tb427.BES40.22')</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACCCATCTTCTGTA-1</th>\n",
       "      <td>48</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.889263</td>\n",
       "      <td>-6.209695</td>\n",
       "      <td>3</td>\n",
       "      <td>('vsg-2-Tb427.BES40.22',)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACGAACATAGGTAA-1</th>\n",
       "      <td>52</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>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-7.084458</td>\n",
       "      <td>5.145591</td>\n",
       "      <td>7</td>\n",
       "      <td>('vsg-15-Tb427.BES134.6', 'vsg-2-Tb427.BES40.2...</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACGAAGTACAGTAA-1</th>\n",
       "      <td>111</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-3.775119</td>\n",
       "      <td>1.836348</td>\n",
       "      <td>5</td>\n",
       "      <td>('vsg-2-Tb427.BES40.22', 'vsg-8-Tb427.BES29.9')</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAAGAACCATGAGAAT-1</th>\n",
       "      <td>52</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-6.715941</td>\n",
       "      <td>4.457271</td>\n",
       "      <td>7</td>\n",
       "      <td>('vsg-2-Tb427.BES40.22', 'vsg-8-Tb427.BES29.9')</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    vsg-2-Tb427.BES40.22  vsg-9-Tb427.BES129.14  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                    49                      0   \n",
       "AAACCCATCTTCTGTA-1                    48                      0   \n",
       "AAACGAACATAGGTAA-1                    52                      0   \n",
       "AAACGAAGTACAGTAA-1                   111                      0   \n",
       "AAAGAACCATGAGAAT-1                    52                      0   \n",
       "\n",
       "                    vsg-6-Tb427.BES15.12  vsg-21-Tb427.BES28.15  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                     0                      0   \n",
       "AAACCCATCTTCTGTA-1                     0                      0   \n",
       "AAACGAACATAGGTAA-1                     0                      0   \n",
       "AAACGAAGTACAGTAA-1                     0                      0   \n",
       "AAAGAACCATGAGAAT-1                     0                      0   \n",
       "\n",
       "                    vsg-18-Tb427.BES98.12  vsg-3-Tb427.BES65.13  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                      0                     0   \n",
       "AAACCCATCTTCTGTA-1                      0                     0   \n",
       "AAACGAACATAGGTAA-1                      0                     0   \n",
       "AAACGAAGTACAGTAA-1                      0                     0   \n",
       "AAAGAACCATGAGAAT-1                      0                     0   \n",
       "\n",
       "                    vsg-14-Tb427.BES64.2  vsg-15-Tb427.BES134.6  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                     0                      0   \n",
       "AAACCCATCTTCTGTA-1                     0                      0   \n",
       "AAACGAACATAGGTAA-1                     0                      2   \n",
       "AAACGAAGTACAGTAA-1                     0                      0   \n",
       "AAAGAACCATGAGAAT-1                     0                      0   \n",
       "\n",
       "                    vsg-16-Tb427.BES122.11  vsg-8-Tb427.BES29.9  ...  \\\n",
       "index                                                            ...   \n",
       "AAACCCACAATAGTGA-1                       0                    0  ...   \n",
       "AAACCCATCTTCTGTA-1                       0                    0  ...   \n",
       "AAACGAACATAGGTAA-1                       0                    4  ...   \n",
       "AAACGAAGTACAGTAA-1                       0                    1  ...   \n",
       "AAAGAACCATGAGAAT-1                       0                    5  ...   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-653  vsg-mes-Tb427VSG-1954  \\\n",
       "index                                                             \n",
       "AAACCCACAATAGTGA-1                     0                      0   \n",
       "AAACCCATCTTCTGTA-1                     0                      0   \n",
       "AAACGAACATAGGTAA-1                     0                      0   \n",
       "AAACGAAGTACAGTAA-1                     0                      0   \n",
       "AAAGAACCATGAGAAT-1                     0                      0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-636  vsg-mes-Tb427VSG-559  \\\n",
       "index                                                            \n",
       "AAACCCACAATAGTGA-1                     0                     0   \n",
       "AAACCCATCTTCTGTA-1                     0                     0   \n",
       "AAACGAACATAGGTAA-1                     0                     0   \n",
       "AAACGAAGTACAGTAA-1                     0                     0   \n",
       "AAAGAACCATGAGAAT-1                     0                     0   \n",
       "\n",
       "                    vsg-mes-Tb427VSG-3591     comp1     comp2  clusters  \\\n",
       "index                                                                     \n",
       "AAACCCACAATAGTGA-1                      0  0.066402  2.499921         4   \n",
       "AAACCCATCTTCTGTA-1                      0  0.889263 -6.209695         3   \n",
       "AAACGAACATAGGTAA-1                      0 -7.084458  5.145591         7   \n",
       "AAACGAAGTACAGTAA-1                      0 -3.775119  1.836348         5   \n",
       "AAAGAACCATGAGAAT-1                      0 -6.715941  4.457271         7   \n",
       "\n",
       "                                                            vsg_class  \\\n",
       "index                                                                   \n",
       "AAACCCACAATAGTGA-1  ('vsg-17-Tb427.BES56.13', 'vsg-2-Tb427.BES40.22')   \n",
       "AAACCCATCTTCTGTA-1                          ('vsg-2-Tb427.BES40.22',)   \n",
       "AAACGAACATAGGTAA-1  ('vsg-15-Tb427.BES134.6', 'vsg-2-Tb427.BES40.2...   \n",
       "AAACGAAGTACAGTAA-1    ('vsg-2-Tb427.BES40.22', 'vsg-8-Tb427.BES29.9')   \n",
       "AAAGAACCATGAGAAT-1    ('vsg-2-Tb427.BES40.22', 'vsg-8-Tb427.BES29.9')   \n",
       "\n",
       "                    size_class  \n",
       "index                           \n",
       "AAACCCACAATAGTGA-1           2  \n",
       "AAACCCATCTTCTGTA-1           1  \n",
       "AAACGAACATAGGTAA-1           3  \n",
       "AAACGAAGTACAGTAA-1           2  \n",
       "AAAGAACCATGAGAAT-1           2  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "df = pd.read_csv('new_count_vsg_vex1_2.csv',index_col =[0])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "aaa2ee68-8bbd-42b8-979b-c1bee6653b20",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(figsize=(8,8))\n",
    "sns.scatterplot(data=df, x='comp1',y='comp2', hue='size_class', ax=ax,\n",
    "                alpha=0.5, s=10,palette ='Paired')\n",
    "ax.legend(title='Size Class')\n",
    "ax.set_xlabel('UMAP component 1')   \n",
    "ax.set_ylabel('UMAP component 2')\n",
    "sns.despine(fig,trim=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3b7bd5ef-89fd-42bd-bfab-bc5fbb2c6fb6",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:miniconda3-seurat2]",
   "language": "python",
   "name": "conda-env-miniconda3-seurat2-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": "3.9.7"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "165px"
   },
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}