{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "55e261bb",
   "metadata": {},
   "source": [
    "## Visuailzing multiple enrichment analysis results\n",
    "\n",
    "Utilizing GSEApy, we present an example of visualizing the outcomes of multiple enrichment analyses. Here, we employ a dataset from a study that examined transcriptomic alterations induced by BK polyomavirus infection in renal tubular epithelial cells ([Assetta et al. 2019](https://doi.org/10.1128/mbio.02354-19))."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ce29a422",
   "metadata": {},
   "outputs": [],
   "source": [
    "import gseapy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2743dfe7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pickle as pkl\n",
    "\n",
    "from pydeseq2.dds import DeseqDataSet\n",
    "from pydeseq2.ds import DeseqStats\n",
    "from pydeseq2.utils import load_example_data\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "61388295",
   "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>A1BG</th>\n",
       "      <th>A1BG-AS1</th>\n",
       "      <th>A1CF</th>\n",
       "      <th>A2M</th>\n",
       "      <th>A2M-AS1</th>\n",
       "      <th>A2ML1</th>\n",
       "      <th>A2MP1</th>\n",
       "      <th>A3GALT2</th>\n",
       "      <th>A4GALT</th>\n",
       "      <th>A4GNT</th>\n",
       "      <th>...</th>\n",
       "      <th>ZWILCH</th>\n",
       "      <th>ZWINT</th>\n",
       "      <th>ZXDA</th>\n",
       "      <th>ZXDB</th>\n",
       "      <th>ZXDC</th>\n",
       "      <th>ZYG11A</th>\n",
       "      <th>ZYG11B</th>\n",
       "      <th>ZYX</th>\n",
       "      <th>ZZEF1</th>\n",
       "      <th>ZZZ3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SRR9967595</th>\n",
       "      <td>20</td>\n",
       "      <td>81</td>\n",
       "      <td>1</td>\n",
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       "      <td>22</td>\n",
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       "      <td>669</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1055</td>\n",
       "      <td>1034</td>\n",
       "      <td>295</td>\n",
       "      <td>363</td>\n",
       "      <td>1053</td>\n",
       "      <td>96</td>\n",
       "      <td>2297</td>\n",
       "      <td>2381</td>\n",
       "      <td>1801</td>\n",
       "      <td>2806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SRR9967596</th>\n",
       "      <td>27</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
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       "      <td>504</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>901</td>\n",
       "      <td>1023</td>\n",
       "      <td>299</td>\n",
       "      <td>293</td>\n",
       "      <td>868</td>\n",
       "      <td>80</td>\n",
       "      <td>1998</td>\n",
       "      <td>2238</td>\n",
       "      <td>1521</td>\n",
       "      <td>2481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SRR9967597</th>\n",
       "      <td>15</td>\n",
       "      <td>82</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>513</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1307</td>\n",
       "      <td>1564</td>\n",
       "      <td>257</td>\n",
       "      <td>409</td>\n",
       "      <td>1040</td>\n",
       "      <td>84</td>\n",
       "      <td>2527</td>\n",
       "      <td>1895</td>\n",
       "      <td>1939</td>\n",
       "      <td>2901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SRR9967598</th>\n",
       "      <td>9</td>\n",
       "      <td>44</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>488</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>978</td>\n",
       "      <td>1779</td>\n",
       "      <td>66</td>\n",
       "      <td>123</td>\n",
       "      <td>612</td>\n",
       "      <td>108</td>\n",
       "      <td>1072</td>\n",
       "      <td>858</td>\n",
       "      <td>1228</td>\n",
       "      <td>1927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SRR9967599</th>\n",
       "      <td>23</td>\n",
       "      <td>77</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>721</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1650</td>\n",
       "      <td>2778</td>\n",
       "      <td>135</td>\n",
       "      <td>183</td>\n",
       "      <td>855</td>\n",
       "      <td>121</td>\n",
       "      <td>1769</td>\n",
       "      <td>1016</td>\n",
       "      <td>1484</td>\n",
       "      <td>2843</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29744 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            A1BG  A1BG-AS1  A1CF  A2M  A2M-AS1  A2ML1  A2MP1  A3GALT2  A4GALT   \n",
       "SRR9967595    20        81     1    0       22      0      0        0     669  \\\n",
       "SRR9967596    27        80     1    1       14      0      0        0     504   \n",
       "SRR9967597    15        82     0    3       18      0      0        0     513   \n",
       "SRR9967598     9        44     1    1        7      1      0        0     488   \n",
       "SRR9967599    23        77     0    2       10      0      0        3     721   \n",
       "\n",
       "            A4GNT  ...  ZWILCH  ZWINT  ZXDA  ZXDB  ZXDC  ZYG11A  ZYG11B   ZYX   \n",
       "SRR9967595      0  ...    1055   1034   295   363  1053      96    2297  2381  \\\n",
       "SRR9967596      0  ...     901   1023   299   293   868      80    1998  2238   \n",
       "SRR9967597      0  ...    1307   1564   257   409  1040      84    2527  1895   \n",
       "SRR9967598      0  ...     978   1779    66   123   612     108    1072   858   \n",
       "SRR9967599      1  ...    1650   2778   135   183   855     121    1769  1016   \n",
       "\n",
       "            ZZEF1  ZZZ3  \n",
       "SRR9967595   1801  2806  \n",
       "SRR9967596   1521  2481  \n",
       "SRR9967597   1939  2901  \n",
       "SRR9967598   1228  1927  \n",
       "SRR9967599   1484  2843  \n",
       "\n",
       "[5 rows x 29744 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "count_df = pd.read_csv(\"PRJNA560236_count.txt\", sep=\"\\t\").T\n",
    "count_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2eb2223c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "        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>Run</th>\n",
       "      <th>Assay Type</th>\n",
       "      <th>AvgSpotLen</th>\n",
       "      <th>BioProject</th>\n",
       "      <th>BioSample</th>\n",
       "      <th>cell_source</th>\n",
       "      <th>Cell_type</th>\n",
       "      <th>Center Name</th>\n",
       "      <th>Consent</th>\n",
       "      <th>DATASTORE filetype</th>\n",
       "      <th>...</th>\n",
       "      <th>MBytes</th>\n",
       "      <th>Organism</th>\n",
       "      <th>Platform</th>\n",
       "      <th>ReleaseDate</th>\n",
       "      <th>sample_acc</th>\n",
       "      <th>Sample Name</th>\n",
       "      <th>source_name</th>\n",
       "      <th>SRA Study</th>\n",
       "      <th>time_point</th>\n",
       "      <th>treatment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SRR9967595</th>\n",
       "      <td>SRR9967595</td>\n",
       "      <td>RNA-Seq</td>\n",
       "      <td>100</td>\n",
       "      <td>PRJNA560236</td>\n",
       "      <td>SAMN12572476</td>\n",
       "      <td>13 months old female</td>\n",
       "      <td>Primary Human Renal Epithelial Cells (ATCC)</td>\n",
       "      <td>GEO</td>\n",
       "      <td>public</td>\n",
       "      <td>fastq,sra</td>\n",
       "      <td>...</td>\n",
       "      <td>2404</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>ILLUMINA</td>\n",
       "      <td>2019-08-15T00:00:00Z</td>\n",
       "      <td>SRS5268041</td>\n",
       "      <td>GSM4034946</td>\n",
       "      <td>BK infected cells at 3 days post infection</td>\n",
       "      <td>SRP218354</td>\n",
       "      <td>at 3 days post infection</td>\n",
       "      <td>BK polyomavirus (BKPyV)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SRR9967596</th>\n",
       "      <td>SRR9967596</td>\n",
       "      <td>RNA-Seq</td>\n",
       "      <td>100</td>\n",
       "      <td>PRJNA560236</td>\n",
       "      <td>SAMN12572509</td>\n",
       "      <td>13 months old female</td>\n",
       "      <td>Primary Human Renal Epithelial Cells (ATCC)</td>\n",
       "      <td>GEO</td>\n",
       "      <td>public</td>\n",
       "      <td>fastq,sra</td>\n",
       "      <td>...</td>\n",
       "      <td>1997</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>ILLUMINA</td>\n",
       "      <td>2019-08-15T00:00:00Z</td>\n",
       "      <td>SRS5268042</td>\n",
       "      <td>GSM4034947</td>\n",
       "      <td>BK infected cells at 3 days post infection</td>\n",
       "      <td>SRP218354</td>\n",
       "      <td>at 3 days post infection</td>\n",
       "      <td>BK polyomavirus (BKPyV)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SRR9967597</th>\n",
       "      <td>SRR9967597</td>\n",
       "      <td>RNA-Seq</td>\n",
       "      <td>100</td>\n",
       "      <td>PRJNA560236</td>\n",
       "      <td>SAMN12572508</td>\n",
       "      <td>13 months old female</td>\n",
       "      <td>Primary Human Renal Epithelial Cells (ATCC)</td>\n",
       "      <td>GEO</td>\n",
       "      <td>public</td>\n",
       "      <td>fastq,sra</td>\n",
       "      <td>...</td>\n",
       "      <td>2375</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>ILLUMINA</td>\n",
       "      <td>2019-08-15T00:00:00Z</td>\n",
       "      <td>SRS5268043</td>\n",
       "      <td>GSM4034948</td>\n",
       "      <td>BK infected cells at 3 days post infection</td>\n",
       "      <td>SRP218354</td>\n",
       "      <td>at 3 days post infection</td>\n",
       "      <td>BK polyomavirus (BKPyV)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SRR9967598</th>\n",
       "      <td>SRR9967598</td>\n",
       "      <td>RNA-Seq</td>\n",
       "      <td>100</td>\n",
       "      <td>PRJNA560236</td>\n",
       "      <td>SAMN12572507</td>\n",
       "      <td>13 months old female</td>\n",
       "      <td>Primary Human Renal Epithelial Cells (ATCC)</td>\n",
       "      <td>GEO</td>\n",
       "      <td>public</td>\n",
       "      <td>fastq,sra</td>\n",
       "      <td>...</td>\n",
       "      <td>1921</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>ILLUMINA</td>\n",
       "      <td>2019-08-15T00:00:00Z</td>\n",
       "      <td>SRS5268044</td>\n",
       "      <td>GSM4034949</td>\n",
       "      <td>BK infected cells at 6 days post infection</td>\n",
       "      <td>SRP218354</td>\n",
       "      <td>at 6 days post infection</td>\n",
       "      <td>BK polyomavirus (BKPyV)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SRR9967599</th>\n",
       "      <td>SRR9967599</td>\n",
       "      <td>RNA-Seq</td>\n",
       "      <td>100</td>\n",
       "      <td>PRJNA560236</td>\n",
       "      <td>SAMN12572506</td>\n",
       "      <td>13 months old female</td>\n",
       "      <td>Primary Human Renal Epithelial Cells (ATCC)</td>\n",
       "      <td>GEO</td>\n",
       "      <td>public</td>\n",
       "      <td>fastq,sra</td>\n",
       "      <td>...</td>\n",
       "      <td>2676</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>ILLUMINA</td>\n",
       "      <td>2019-08-15T00:00:00Z</td>\n",
       "      <td>SRS5268045</td>\n",
       "      <td>GSM4034950</td>\n",
       "      <td>BK infected cells at 6 days post infection</td>\n",
       "      <td>SRP218354</td>\n",
       "      <td>at 6 days post infection</td>\n",
       "      <td>BK polyomavirus (BKPyV)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Run Assay Type  AvgSpotLen   BioProject     BioSample   \n",
       "SRR9967595  SRR9967595    RNA-Seq         100  PRJNA560236  SAMN12572476  \\\n",
       "SRR9967596  SRR9967596    RNA-Seq         100  PRJNA560236  SAMN12572509   \n",
       "SRR9967597  SRR9967597    RNA-Seq         100  PRJNA560236  SAMN12572508   \n",
       "SRR9967598  SRR9967598    RNA-Seq         100  PRJNA560236  SAMN12572507   \n",
       "SRR9967599  SRR9967599    RNA-Seq         100  PRJNA560236  SAMN12572506   \n",
       "\n",
       "                     cell_source                                    Cell_type   \n",
       "SRR9967595  13 months old female  Primary Human Renal Epithelial Cells (ATCC)  \\\n",
       "SRR9967596  13 months old female  Primary Human Renal Epithelial Cells (ATCC)   \n",
       "SRR9967597  13 months old female  Primary Human Renal Epithelial Cells (ATCC)   \n",
       "SRR9967598  13 months old female  Primary Human Renal Epithelial Cells (ATCC)   \n",
       "SRR9967599  13 months old female  Primary Human Renal Epithelial Cells (ATCC)   \n",
       "\n",
       "           Center Name Consent DATASTORE filetype  ... MBytes      Organism   \n",
       "SRR9967595         GEO  public          fastq,sra  ...   2404  Homo sapiens  \\\n",
       "SRR9967596         GEO  public          fastq,sra  ...   1997  Homo sapiens   \n",
       "SRR9967597         GEO  public          fastq,sra  ...   2375  Homo sapiens   \n",
       "SRR9967598         GEO  public          fastq,sra  ...   1921  Homo sapiens   \n",
       "SRR9967599         GEO  public          fastq,sra  ...   2676  Homo sapiens   \n",
       "\n",
       "            Platform           ReleaseDate  sample_acc Sample Name   \n",
       "SRR9967595  ILLUMINA  2019-08-15T00:00:00Z  SRS5268041  GSM4034946  \\\n",
       "SRR9967596  ILLUMINA  2019-08-15T00:00:00Z  SRS5268042  GSM4034947   \n",
       "SRR9967597  ILLUMINA  2019-08-15T00:00:00Z  SRS5268043  GSM4034948   \n",
       "SRR9967598  ILLUMINA  2019-08-15T00:00:00Z  SRS5268044  GSM4034949   \n",
       "SRR9967599  ILLUMINA  2019-08-15T00:00:00Z  SRS5268045  GSM4034950   \n",
       "\n",
       "                                           source_name  SRA Study   \n",
       "SRR9967595  BK infected cells at 3 days post infection  SRP218354  \\\n",
       "SRR9967596  BK infected cells at 3 days post infection  SRP218354   \n",
       "SRR9967597  BK infected cells at 3 days post infection  SRP218354   \n",
       "SRR9967598  BK infected cells at 6 days post infection  SRP218354   \n",
       "SRR9967599  BK infected cells at 6 days post infection  SRP218354   \n",
       "\n",
       "                          time_point                treatment  \n",
       "SRR9967595  at 3 days post infection  BK polyomavirus (BKPyV)  \n",
       "SRR9967596  at 3 days post infection  BK polyomavirus (BKPyV)  \n",
       "SRR9967597  at 3 days post infection  BK polyomavirus (BKPyV)  \n",
       "SRR9967598  at 6 days post infection  BK polyomavirus (BKPyV)  \n",
       "SRR9967599  at 6 days post infection  BK polyomavirus (BKPyV)  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clinical_df = pd.read_csv(\"SraRunTable_PRJNA560236.txt\", sep=\",\")\n",
    "clinical_df.index = clinical_df.Run\n",
    "clinical_df.index.name = None\n",
    "candidate = clinical_df[clinical_df[\"time_point\"]==\"at 6 days post infection\"].index\n",
    "candidate = list(set(candidate) & set(count_df.index))\n",
    "clinical_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3a39342b",
   "metadata": {},
   "outputs": [],
   "source": [
    "dds = DeseqDataSet(\n",
    "    counts=count_df.loc[candidate,:],\n",
    "    clinical=clinical_df.loc[candidate,:],\n",
    "    design_factors=\"treatment\", \n",
    "    refit_cooks=True,\n",
    "    n_cpus=8,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4d18e2fb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting size factors...\n",
      "... done in 0.02 seconds.\n",
      "\n",
      "Fitting dispersions...\n",
      "... done in 10.25 seconds.\n",
      "\n",
      "Fitting dispersion trend curve...\n",
      "... done in 11.86 seconds.\n",
      "\n",
      "Fitting MAP dispersions...\n",
      "... done in 10.26 seconds.\n",
      "\n",
      "Fitting LFCs...\n",
      "... done in 3.59 seconds.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "dds.fit_size_factors()\n",
    "dds.fit_genewise_dispersions()\n",
    "dds.fit_dispersion_trend()\n",
    "dds.fit_dispersion_prior()\n",
    "dds.fit_MAP_dispersions()\n",
    "dds.fit_LFC()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d152892b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Refitting 0 outliers.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "dds.calculate_cooks()\n",
    "if dds.refit_cooks:\n",
    "    # Replace outlier counts\n",
    "    dds.refit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fac004ae",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running Wald tests...\n",
      "... done in 4.53 seconds.\n",
      "\n",
      "Log2 fold change & Wald test p-value: treatment BK polyomavirus (BKPyV) vs none (uninfected)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>baseMean</th>\n",
       "      <th>log2FoldChange</th>\n",
       "      <th>lfcSE</th>\n",
       "      <th>stat</th>\n",
       "      <th>pvalue</th>\n",
       "      <th>padj</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A1BG</th>\n",
       "      <td>15.356750</td>\n",
       "      <td>0.019922</td>\n",
       "      <td>0.380606</td>\n",
       "      <td>0.052344</td>\n",
       "      <td>9.582549e-01</td>\n",
       "      <td>0.974228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A1BG-AS1</th>\n",
       "      <td>79.427946</td>\n",
       "      <td>-0.747451</td>\n",
       "      <td>0.292659</td>\n",
       "      <td>-2.554004</td>\n",
       "      <td>1.064922e-02</td>\n",
       "      <td>0.032686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A1CF</th>\n",
       "      <td>0.685369</td>\n",
       "      <td>-1.268784</td>\n",
       "      <td>1.636031</td>\n",
       "      <td>-0.775526</td>\n",
       "      <td>4.380292e-01</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A2M</th>\n",
       "      <td>0.968656</td>\n",
       "      <td>0.189368</td>\n",
       "      <td>1.209550</td>\n",
       "      <td>0.156561</td>\n",
       "      <td>8.755908e-01</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A2M-AS1</th>\n",
       "      <td>12.146683</td>\n",
       "      <td>-1.006216</td>\n",
       "      <td>0.439510</td>\n",
       "      <td>-2.289404</td>\n",
       "      <td>2.205589e-02</td>\n",
       "      <td>0.059017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZYG11A</th>\n",
       "      <td>84.048757</td>\n",
       "      <td>1.337741</td>\n",
       "      <td>0.262999</td>\n",
       "      <td>5.086480</td>\n",
       "      <td>3.647705e-07</td>\n",
       "      <td>0.000004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZYG11B</th>\n",
       "      <td>1863.055526</td>\n",
       "      <td>-0.436978</td>\n",
       "      <td>0.184829</td>\n",
       "      <td>-2.364225</td>\n",
       "      <td>1.806783e-02</td>\n",
       "      <td>0.050254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZYX</th>\n",
       "      <td>1102.044658</td>\n",
       "      <td>-0.545409</td>\n",
       "      <td>0.301693</td>\n",
       "      <td>-1.807829</td>\n",
       "      <td>7.063307e-02</td>\n",
       "      <td>0.147662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZZEF1</th>\n",
       "      <td>1504.948093</td>\n",
       "      <td>-0.016638</td>\n",
       "      <td>0.169712</td>\n",
       "      <td>-0.098035</td>\n",
       "      <td>9.219047e-01</td>\n",
       "      <td>0.951360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZZZ3</th>\n",
       "      <td>2551.864972</td>\n",
       "      <td>0.034200</td>\n",
       "      <td>0.137628</td>\n",
       "      <td>0.248499</td>\n",
       "      <td>8.037484e-01</td>\n",
       "      <td>0.872939</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29744 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             baseMean  log2FoldChange     lfcSE      stat        pvalue   \n",
       "A1BG        15.356750        0.019922  0.380606  0.052344  9.582549e-01  \\\n",
       "A1BG-AS1    79.427946       -0.747451  0.292659 -2.554004  1.064922e-02   \n",
       "A1CF         0.685369       -1.268784  1.636031 -0.775526  4.380292e-01   \n",
       "A2M          0.968656        0.189368  1.209550  0.156561  8.755908e-01   \n",
       "A2M-AS1     12.146683       -1.006216  0.439510 -2.289404  2.205589e-02   \n",
       "...               ...             ...       ...       ...           ...   \n",
       "ZYG11A      84.048757        1.337741  0.262999  5.086480  3.647705e-07   \n",
       "ZYG11B    1863.055526       -0.436978  0.184829 -2.364225  1.806783e-02   \n",
       "ZYX       1102.044658       -0.545409  0.301693 -1.807829  7.063307e-02   \n",
       "ZZEF1     1504.948093       -0.016638  0.169712 -0.098035  9.219047e-01   \n",
       "ZZZ3      2551.864972        0.034200  0.137628  0.248499  8.037484e-01   \n",
       "\n",
       "              padj  \n",
       "A1BG      0.974228  \n",
       "A1BG-AS1  0.032686  \n",
       "A1CF           NaN  \n",
       "A2M            NaN  \n",
       "A2M-AS1   0.059017  \n",
       "...            ...  \n",
       "ZYG11A    0.000004  \n",
       "ZYG11B    0.050254  \n",
       "ZYX       0.147662  \n",
       "ZZEF1     0.951360  \n",
       "ZZZ3      0.872939  \n",
       "\n",
       "[29744 rows x 6 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "stat_res = DeseqStats(dds, alpha=0.05,contrast=[\"treatment\",\"BK polyomavirus (BKPyV)\",\"none (uninfected)\"])\n",
    "stat_res.run_wald_test()\n",
    "if stat_res.cooks_filter:\n",
    "    stat_res._cooks_filtering()\n",
    "stat_res.p_values\n",
    "if stat_res.independent_filter:\n",
    "    stat_res._independent_filtering()\n",
    "else:\n",
    "    stat_res._p_value_adjustment()\n",
    "stat_res.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9297514d",
   "metadata": {},
   "outputs": [],
   "source": [
    "stat_res_summary = stat_res.results_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c360aa66",
   "metadata": {},
   "outputs": [],
   "source": [
    "sig_genes_up = list(stat_res_summary[(stat_res_summary.padj<0.05) & (stat_res_summary.log2FoldChange>0)].index)\n",
    "sig_genes_down = list(stat_res_summary[(stat_res_summary.padj<0.05) & (stat_res_summary.log2FoldChange<0)].index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "0300f999",
   "metadata": {},
   "outputs": [],
   "source": [
    "enr_res_up = gseapy.enrichr(gene_list=sig_genes_up,\n",
    "                     organism='Human',\n",
    "                     gene_sets='KEGG_2021_Human',\n",
    "                     cutoff = 0.05)\n",
    "enr_res_down = gseapy.enrichr(gene_list=sig_genes_down,\n",
    "                     organism='Human',\n",
    "                     gene_sets='KEGG_2021_Human',\n",
    "                     cutoff = 0.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9bf54909",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='$- \\\\log_{10}$ (Adjusted P-value)'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gseapy.barplot(enr_res_up.res2d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "60aaf239",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGBA size=1301x757>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import requests_cache\n",
    "import pykegg\n",
    "from PIL import Image\n",
    "## Cache all the downloaded files\n",
    "requests_cache.install_cache('pykegg_cache')\n",
    "\n",
    "## Single result\n",
    "Image.fromarray(pykegg.visualize_gseapy(enr_res_up,\n",
    "                                 colors=[\"#ff0000\"],\n",
    "                                 pathway_name=\"p53 signaling pathway\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "06d1ad55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGBA size=1301x757>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Multiple results\n",
    "Image.fromarray(pykegg.visualize_gseapy([enr_res_up, enr_res_down],\n",
    "                                 colors=[\"#ff0000\", \"#0000ff\"],\n",
    "                                 pathway_name=\"p53 signaling pathway\"))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}