Examples/build_multidataset_reference_vignette.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "af38c5d0-989f-40a5-9388-58fd98f1d045",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import os\n",
    "import scanpy as sc\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from starcat import BuildConsensusReference, starCAT\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0d1117e-b1ee-4ab4-989d-f2314437829c",
   "metadata": {},
   "source": [
    "Provides example code for building a new starCAT reference based on cNMF results from multiple datasets.\n",
    "\n",
    "This tutorial does not run cNMF itself but uses results that are already saved. For more information about running cNMF, see the [build_reference_vignette.ipynb](./build_reference_vignette.ipynb) example and refer to the [cNMF github page](https://github.com/dylkot/cNMF/tree/master)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34d913a6-6183-4f1c-9b1b-0c8276541b6e",
   "metadata": {},
   "source": [
    "# Download the cNMF results and example query data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f778725b-de7d-4b89-a6ee-78ecc886ffd7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2024-08-23 17:20:16--  https://zenodo.org/records/13368101/files/Example_refbuilder.tar.gz\n",
      "Resolving zenodo.org (zenodo.org)... 188.184.98.238, 188.184.103.159, 188.185.79.172\n",
      "Connecting to zenodo.org (zenodo.org)|188.184.98.238|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 24294951 (23M) [application/octet-stream]\n",
      "Saving to: ‘Example_refbuilder.tar.gz’\n",
      "\n",
      "Example_refbuilder. 100%[===================>]  23.17M  2.63MB/s    in 9.6s    \n",
      "\n",
      "2024-08-23 17:20:26 (2.41 MB/s) - ‘Example_refbuilder.tar.gz’ saved [24294951/24294951]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "! wget https://zenodo.org/records/13368101/files/Example_refbuilder.tar.gz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "54b1b42c-b77e-4f1e-a187-8f696507a70d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x Example_refbuilder/\n",
      "x Example_refbuilder/UKCOVID.20231005.Iter200/\n",
      "x Example_refbuilder/UKCOVID.20231005.Iter200/cnmf_tmp/\n",
      "x Example_refbuilder/UKCOVID.20231005.Iter200/cnmf_tmp/UKCOVID.20231005.Iter200.tpm_stats.df.npz\n",
      "x Example_refbuilder/UKCOVID.20231005.Iter200/UKCOVID.20231005.Iter200.overdispersed_genes.txt\n",
      "x Example_refbuilder/UKCOVID.20231005.Iter200/UKCOVID.20231005.Iter200.gene_spectra_tpm.k_44.dt_0_2.txt\n",
      "x Example_refbuilder/UKCOVID.20231005.Iter200/UKCOVID.20231005.Iter200.gene_spectra_score.k_44.dt_0_2.txt\n",
      "x Example_refbuilder/HIVVaccine.20230907.Iter200/\n",
      "x Example_refbuilder/HIVVaccine.20230907.Iter200/cnmf_tmp/\n",
      "x Example_refbuilder/HIVVaccine.20230907.Iter200/cnmf_tmp/HIVVaccine.20230907.Iter200.tpm_stats.df.npz\n",
      "x Example_refbuilder/HIVVaccine.20230907.Iter200/HIVVaccine.20230907.Iter200.overdispersed_genes.txt\n",
      "x Example_refbuilder/HIVVaccine.20230907.Iter200/HIVVaccine.20230907.Iter200.gene_spectra_tpm.k_31.dt_0_15.txt\n",
      "x Example_refbuilder/HIVVaccine.20230907.Iter200/HIVVaccine.20230907.Iter200.gene_spectra_score.k_31.dt_0_15.txt\n",
      "x Example_refbuilder/COMBAT.20230927.Iter200/\n",
      "x Example_refbuilder/COMBAT.20230927.Iter200/cnmf_tmp/\n",
      "x Example_refbuilder/COMBAT.20230927.Iter200/cnmf_tmp/COMBAT.20230927.Iter200.tpm_stats.df.npz\n",
      "x Example_refbuilder/COMBAT.20230927.Iter200/COMBAT.20230927.Iter200.overdispersed_genes.txt\n",
      "x Example_refbuilder/COMBAT.20230927.Iter200/COMBAT.20230927.Iter200.gene_spectra_tpm.k_35.dt_0_15.txt\n",
      "x Example_refbuilder/COMBAT.20230927.Iter200/COMBAT.20230927.Iter200.gene_spectra_score.k_35.dt_0_15.txt\n",
      "x Example_refbuilder/example_memoryT_query.h5ad\n"
     ]
    }
   ],
   "source": [
    "! tar -zxvf Example_refbuilder.tar.gz   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3bb7a5b9-f4ab-472d-b661-3685eae7ad40",
   "metadata": {},
   "outputs": [],
   "source": [
    "! rm Example_refbuilder.tar.gz   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d5f433d5-566c-4092-86d3-4b9af187e713",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total 43432\n",
      "drwxr-xr-x@ 6 dkotliar  staff   192B Jul 23 18:36 \u001b[34m.\u001b[m\u001b[m\n",
      "drwxr-xr-x@ 8 dkotliar  staff   256B Aug 23 17:20 \u001b[34m..\u001b[m\u001b[m\n",
      "drwxr-x---@ 6 dkotliar  staff   192B Jul 23 20:12 \u001b[34mCOMBAT.20230927.Iter200\u001b[m\u001b[m\n",
      "drwxr-x---@ 6 dkotliar  staff   192B Jul 23 20:12 \u001b[34mHIVVaccine.20230907.Iter200\u001b[m\u001b[m\n",
      "drwxr-x---@ 6 dkotliar  staff   192B Jul 23 20:12 \u001b[34mUKCOVID.20231005.Iter200\u001b[m\u001b[m\n",
      "-rw-r--r--@ 1 dkotliar  staff    21M Jul 23 20:22 example_memoryT_query.h5ad\n"
     ]
    }
   ],
   "source": [
    "! ls -lah Example_refbuilder"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7242f020-6272-4978-b41d-bd4bed6cf30c",
   "metadata": {},
   "source": [
    "# Run the code to merge the cluster the spectra from the multiple cNMF runs into consensus gene expression programs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4b5da67c-e0fa-493d-b042-5c772f7eca54",
   "metadata": {},
   "outputs": [],
   "source": [
    "cnmf_paths = ['Example_refbuilder/COMBAT.20230927.Iter200/',\n",
    "              'Example_refbuilder/HIVVaccine.20230907.Iter200',\n",
    "              'Example_refbuilder/UKCOVID.20231005.Iter200']\n",
    "Ks = [35, 31, 44]\n",
    "dts = [0.15, 0.15, 0.2]\n",
    "outdir = './Example_refbuilder'\n",
    "prefix = 'starcat_ref'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d1507fcd-020e-442a-8c90-1d1f0de22a87",
   "metadata": {},
   "outputs": [],
   "source": [
    "refbuilder = BuildConsensusReference(cnmf_paths, ks=Ks, density_thresholds=dts,\n",
    "                                    output_dir=outdir, prefix=prefix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a2e52d33-01b6-41ab-a410-5a0e1b941907",
   "metadata": {},
   "outputs": [],
   "source": [
    "clus_df, spectra_tpm_grouped, spectra_scores_grouped, hvgs_union, top_genes = refbuilder.cluster_cnmf_results()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "238b0048-43a6-4ed9-bf5f-4cfdfc947541",
   "metadata": {},
   "source": [
    "# Look at the results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c803edfc-18f9-4188-8e0f-f1aad71b51a9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[34mCOMBAT.20230927.Iter200\u001b[m\u001b[m\n",
      "\u001b[34mHIVVaccine.20230907.Iter200\u001b[m\u001b[m\n",
      "\u001b[34mUKCOVID.20231005.Iter200\u001b[m\u001b[m\n",
      "example_memoryT_query.h5ad\n",
      "starcat_refstarcat_consensus_clustering.filtered.txt\n",
      "starcat_refstarcat_consensus_clustering.txt\n",
      "starcat_refstarcat_consensus_spectra_normalized.filtered.txt\n",
      "starcat_refstarcat_consensus_spectra_normalized.txt\n",
      "starcat_refstarcat_consensus_spectra_normalized_allgenes.filtered.txt\n",
      "starcat_refstarcat_consensus_spectra_normalized_allgenes.txt\n",
      "starcat_refstarcat_consensus_spectra_score.filtered.txt\n",
      "starcat_refstarcat_consensus_spectra_score.txt\n",
      "starcat_refstarcat_overdispersed_genes_union.txt\n"
     ]
    }
   ],
   "source": [
    "! ls Example_refbuilder"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39ddc3ae-4134-4c27-9b5f-5ba54fdbdc79",
   "metadata": {},
   "source": [
    "Output files have been saved in the Example_Refbuilder directory. The main one that is the input to starCAT is:\n",
    "\n",
    "- ```starcat_refstarcat_consensus_spectra_normalized.filtered.txt``` - average cGEP spectra in variance normalized units subset to high variance genes. This excludes singletons. This is the default spectra we would use for starCAT.\n",
    "\n",
    "If you don't want to exclude singletons, you can use the following instead:\n",
    "\n",
    "- ```starcat_refstarcat_consensus_spectra_normalized.txt```\n",
    "\n",
    "Other useful output files are:\n",
    "- ```starcat_refstarcat_consensus_spectra_score.filtered.txt``` - average of spectra scores for non-singleton cGEPs. Can be used to identify cGEP marker genes\n",
    "- ```starcat_refstarcat_consensus_clustering.filtered.txt``` - table showing which programs from each cNMF run clustered together and were merged\n",
    "- ```starcat_refstarcat_overdispersed_genes_union.txt``` - list of high variance genes from the union of the reference datasets\n",
    "- ```starcat_refstarcat_consensus_spectra_normalized_allgenes.filtered.txt``` - same as the average cGEP spectra above but including all genes and not just high variance ones"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea1f5ba7-0bf3-4ea1-9a76-687b1ef6ad19",
   "metadata": {},
   "source": [
    "We can look at the unfiltered ```starcat_refstarcat_consensus_clustering.txt``` results below which is stored in the clus_df variable:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5871a536-7c54-4d4b-a16b-071f5dc9e64d",
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>COMBAT.20230927.Iter200</th>\n",
       "      <th>HIVVaccine.20230907.Iter200</th>\n",
       "      <th>UKCOVID.20231005.Iter200</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>cGEP1</th>\n",
       "      <td>COMBAT.20230927.Iter200:23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP2</th>\n",
       "      <td>COMBAT.20230927.Iter200:10</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:10</td>\n",
       "      <td>UKCOVID.20231005.Iter200:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP3</th>\n",
       "      <td>COMBAT.20230927.Iter200:15</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:24</td>\n",
       "      <td>UKCOVID.20231005.Iter200:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP4</th>\n",
       "      <td>COMBAT.20230927.Iter200:25</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:25</td>\n",
       "      <td>UKCOVID.20231005.Iter200:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP5</th>\n",
       "      <td>COMBAT.20230927.Iter200:29</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:30</td>\n",
       "      <td>UKCOVID.20231005.Iter200:35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP6</th>\n",
       "      <td>COMBAT.20230927.Iter200:6</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:9</td>\n",
       "      <td>UKCOVID.20231005.Iter200:3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP7</th>\n",
       "      <td>COMBAT.20230927.Iter200:13</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:21</td>\n",
       "      <td>UKCOVID.20231005.Iter200:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP8</th>\n",
       "      <td>COMBAT.20230927.Iter200:1</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:3</td>\n",
       "      <td>UKCOVID.20231005.Iter200:2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP9</th>\n",
       "      <td>COMBAT.20230927.Iter200:21</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:16</td>\n",
       "      <td>UKCOVID.20231005.Iter200:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP10</th>\n",
       "      <td>COMBAT.20230927.Iter200:33</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:31</td>\n",
       "      <td>UKCOVID.20231005.Iter200:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP11</th>\n",
       "      <td>COMBAT.20230927.Iter200:22</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:27</td>\n",
       "      <td>UKCOVID.20231005.Iter200:31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP12</th>\n",
       "      <td>COMBAT.20230927.Iter200:2</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:8</td>\n",
       "      <td>UKCOVID.20231005.Iter200:4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP13</th>\n",
       "      <td>COMBAT.20230927.Iter200:14</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:18</td>\n",
       "      <td>UKCOVID.20231005.Iter200:20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP14</th>\n",
       "      <td>COMBAT.20230927.Iter200:20</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:19</td>\n",
       "      <td>UKCOVID.20231005.Iter200:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP15</th>\n",
       "      <td>COMBAT.20230927.Iter200:16</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:12</td>\n",
       "      <td>UKCOVID.20231005.Iter200:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP16</th>\n",
       "      <td>COMBAT.20230927.Iter200:31</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:29</td>\n",
       "      <td>UKCOVID.20231005.Iter200:34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP17</th>\n",
       "      <td>COMBAT.20230927.Iter200:8</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:5</td>\n",
       "      <td>UKCOVID.20231005.Iter200:8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP18</th>\n",
       "      <td>COMBAT.20230927.Iter200:3</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:17</td>\n",
       "      <td>UKCOVID.20231005.Iter200:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP19</th>\n",
       "      <td>COMBAT.20230927.Iter200:9</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:15</td>\n",
       "      <td>UKCOVID.20231005.Iter200:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP20</th>\n",
       "      <td>NaN</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:1</td>\n",
       "      <td>UKCOVID.20231005.Iter200:1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP21</th>\n",
       "      <td>COMBAT.20230927.Iter200:7</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:11</td>\n",
       "      <td>UKCOVID.20231005.Iter200:18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP22</th>\n",
       "      <td>COMBAT.20230927.Iter200:26</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:28</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP23</th>\n",
       "      <td>COMBAT.20230927.Iter200:5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP24</th>\n",
       "      <td>NaN</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:2</td>\n",
       "      <td>UKCOVID.20231005.Iter200:9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP25</th>\n",
       "      <td>COMBAT.20230927.Iter200:17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP26</th>\n",
       "      <td>COMBAT.20230927.Iter200:4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP27</th>\n",
       "      <td>NaN</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:14</td>\n",
       "      <td>UKCOVID.20231005.Iter200:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP28</th>\n",
       "      <td>COMBAT.20230927.Iter200:24</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:26</td>\n",
       "      <td>UKCOVID.20231005.Iter200:37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP29</th>\n",
       "      <td>COMBAT.20230927.Iter200:18</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:23</td>\n",
       "      <td>UKCOVID.20231005.Iter200:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP30</th>\n",
       "      <td>COMBAT.20230927.Iter200:11</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:13</td>\n",
       "      <td>UKCOVID.20231005.Iter200:5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP31</th>\n",
       "      <td>COMBAT.20230927.Iter200:32</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP32</th>\n",
       "      <td>NaN</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:7</td>\n",
       "      <td>UKCOVID.20231005.Iter200:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP33</th>\n",
       "      <td>COMBAT.20230927.Iter200:35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP34</th>\n",
       "      <td>COMBAT.20230927.Iter200:12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP35</th>\n",
       "      <td>COMBAT.20230927.Iter200:19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP36</th>\n",
       "      <td>COMBAT.20230927.Iter200:27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP37</th>\n",
       "      <td>COMBAT.20230927.Iter200:28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP38</th>\n",
       "      <td>COMBAT.20230927.Iter200:30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP39</th>\n",
       "      <td>COMBAT.20230927.Iter200:34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP40</th>\n",
       "      <td>NaN</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP41</th>\n",
       "      <td>NaN</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:6</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP42</th>\n",
       "      <td>NaN</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:20</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP43</th>\n",
       "      <td>NaN</td>\n",
       "      <td>HIVVaccine.20230907.Iter200:22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP44</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP45</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP46</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP47</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP48</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP49</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP50</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP51</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP52</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP53</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP54</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cGEP55</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UKCOVID.20231005.Iter200:44</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           COMBAT.20230927.Iter200     HIVVaccine.20230907.Iter200  \\\n",
       "cGEP1   COMBAT.20230927.Iter200:23                             NaN   \n",
       "cGEP2   COMBAT.20230927.Iter200:10  HIVVaccine.20230907.Iter200:10   \n",
       "cGEP3   COMBAT.20230927.Iter200:15  HIVVaccine.20230907.Iter200:24   \n",
       "cGEP4   COMBAT.20230927.Iter200:25  HIVVaccine.20230907.Iter200:25   \n",
       "cGEP5   COMBAT.20230927.Iter200:29  HIVVaccine.20230907.Iter200:30   \n",
       "cGEP6    COMBAT.20230927.Iter200:6   HIVVaccine.20230907.Iter200:9   \n",
       "cGEP7   COMBAT.20230927.Iter200:13  HIVVaccine.20230907.Iter200:21   \n",
       "cGEP8    COMBAT.20230927.Iter200:1   HIVVaccine.20230907.Iter200:3   \n",
       "cGEP9   COMBAT.20230927.Iter200:21  HIVVaccine.20230907.Iter200:16   \n",
       "cGEP10  COMBAT.20230927.Iter200:33  HIVVaccine.20230907.Iter200:31   \n",
       "cGEP11  COMBAT.20230927.Iter200:22  HIVVaccine.20230907.Iter200:27   \n",
       "cGEP12   COMBAT.20230927.Iter200:2   HIVVaccine.20230907.Iter200:8   \n",
       "cGEP13  COMBAT.20230927.Iter200:14  HIVVaccine.20230907.Iter200:18   \n",
       "cGEP14  COMBAT.20230927.Iter200:20  HIVVaccine.20230907.Iter200:19   \n",
       "cGEP15  COMBAT.20230927.Iter200:16  HIVVaccine.20230907.Iter200:12   \n",
       "cGEP16  COMBAT.20230927.Iter200:31  HIVVaccine.20230907.Iter200:29   \n",
       "cGEP17   COMBAT.20230927.Iter200:8   HIVVaccine.20230907.Iter200:5   \n",
       "cGEP18   COMBAT.20230927.Iter200:3  HIVVaccine.20230907.Iter200:17   \n",
       "cGEP19   COMBAT.20230927.Iter200:9  HIVVaccine.20230907.Iter200:15   \n",
       "cGEP20                         NaN   HIVVaccine.20230907.Iter200:1   \n",
       "cGEP21   COMBAT.20230927.Iter200:7  HIVVaccine.20230907.Iter200:11   \n",
       "cGEP22  COMBAT.20230927.Iter200:26  HIVVaccine.20230907.Iter200:28   \n",
       "cGEP23   COMBAT.20230927.Iter200:5                             NaN   \n",
       "cGEP24                         NaN   HIVVaccine.20230907.Iter200:2   \n",
       "cGEP25  COMBAT.20230927.Iter200:17                             NaN   \n",
       "cGEP26   COMBAT.20230927.Iter200:4                             NaN   \n",
       "cGEP27                         NaN  HIVVaccine.20230907.Iter200:14   \n",
       "cGEP28  COMBAT.20230927.Iter200:24  HIVVaccine.20230907.Iter200:26   \n",
       "cGEP29  COMBAT.20230927.Iter200:18  HIVVaccine.20230907.Iter200:23   \n",
       "cGEP30  COMBAT.20230927.Iter200:11  HIVVaccine.20230907.Iter200:13   \n",
       "cGEP31  COMBAT.20230927.Iter200:32                             NaN   \n",
       "cGEP32                         NaN   HIVVaccine.20230907.Iter200:7   \n",
       "cGEP33  COMBAT.20230927.Iter200:35                             NaN   \n",
       "cGEP34  COMBAT.20230927.Iter200:12                             NaN   \n",
       "cGEP35  COMBAT.20230927.Iter200:19                             NaN   \n",
       "cGEP36  COMBAT.20230927.Iter200:27                             NaN   \n",
       "cGEP37  COMBAT.20230927.Iter200:28                             NaN   \n",
       "cGEP38  COMBAT.20230927.Iter200:30                             NaN   \n",
       "cGEP39  COMBAT.20230927.Iter200:34                             NaN   \n",
       "cGEP40                         NaN   HIVVaccine.20230907.Iter200:4   \n",
       "cGEP41                         NaN   HIVVaccine.20230907.Iter200:6   \n",
       "cGEP42                         NaN  HIVVaccine.20230907.Iter200:20   \n",
       "cGEP43                         NaN  HIVVaccine.20230907.Iter200:22   \n",
       "cGEP44                         NaN                             NaN   \n",
       "cGEP45                         NaN                             NaN   \n",
       "cGEP46                         NaN                             NaN   \n",
       "cGEP47                         NaN                             NaN   \n",
       "cGEP48                         NaN                             NaN   \n",
       "cGEP49                         NaN                             NaN   \n",
       "cGEP50                         NaN                             NaN   \n",
       "cGEP51                         NaN                             NaN   \n",
       "cGEP52                         NaN                             NaN   \n",
       "cGEP53                         NaN                             NaN   \n",
       "cGEP54                         NaN                             NaN   \n",
       "cGEP55                         NaN                             NaN   \n",
       "\n",
       "           UKCOVID.20231005.Iter200  \n",
       "cGEP1   UKCOVID.20231005.Iter200:30  \n",
       "cGEP2   UKCOVID.20231005.Iter200:15  \n",
       "cGEP3   UKCOVID.20231005.Iter200:17  \n",
       "cGEP4   UKCOVID.20231005.Iter200:27  \n",
       "cGEP5   UKCOVID.20231005.Iter200:35  \n",
       "cGEP6    UKCOVID.20231005.Iter200:3  \n",
       "cGEP7   UKCOVID.20231005.Iter200:24  \n",
       "cGEP8    UKCOVID.20231005.Iter200:2  \n",
       "cGEP9   UKCOVID.20231005.Iter200:26  \n",
       "cGEP10  UKCOVID.20231005.Iter200:40  \n",
       "cGEP11  UKCOVID.20231005.Iter200:31  \n",
       "cGEP12   UKCOVID.20231005.Iter200:4  \n",
       "cGEP13  UKCOVID.20231005.Iter200:20  \n",
       "cGEP14  UKCOVID.20231005.Iter200:29  \n",
       "cGEP15  UKCOVID.20231005.Iter200:25  \n",
       "cGEP16  UKCOVID.20231005.Iter200:34  \n",
       "cGEP17   UKCOVID.20231005.Iter200:8  \n",
       "cGEP18  UKCOVID.20231005.Iter200:13  \n",
       "cGEP19  UKCOVID.20231005.Iter200:10  \n",
       "cGEP20   UKCOVID.20231005.Iter200:1  \n",
       "cGEP21  UKCOVID.20231005.Iter200:18  \n",
       "cGEP22                          NaN  \n",
       "cGEP23  UKCOVID.20231005.Iter200:21  \n",
       "cGEP24   UKCOVID.20231005.Iter200:9  \n",
       "cGEP25  UKCOVID.20231005.Iter200:28  \n",
       "cGEP26  UKCOVID.20231005.Iter200:19  \n",
       "cGEP27  UKCOVID.20231005.Iter200:12  \n",
       "cGEP28  UKCOVID.20231005.Iter200:37  \n",
       "cGEP29  UKCOVID.20231005.Iter200:11  \n",
       "cGEP30   UKCOVID.20231005.Iter200:5  \n",
       "cGEP31  UKCOVID.20231005.Iter200:39  \n",
       "cGEP32  UKCOVID.20231005.Iter200:14  \n",
       "cGEP33  UKCOVID.20231005.Iter200:38  \n",
       "cGEP34                          NaN  \n",
       "cGEP35                          NaN  \n",
       "cGEP36                          NaN  \n",
       "cGEP37                          NaN  \n",
       "cGEP38                          NaN  \n",
       "cGEP39                          NaN  \n",
       "cGEP40                          NaN  \n",
       "cGEP41                          NaN  \n",
       "cGEP42                          NaN  \n",
       "cGEP43                          NaN  \n",
       "cGEP44   UKCOVID.20231005.Iter200:6  \n",
       "cGEP45   UKCOVID.20231005.Iter200:7  \n",
       "cGEP46  UKCOVID.20231005.Iter200:16  \n",
       "cGEP47  UKCOVID.20231005.Iter200:22  \n",
       "cGEP48  UKCOVID.20231005.Iter200:23  \n",
       "cGEP49  UKCOVID.20231005.Iter200:32  \n",
       "cGEP50  UKCOVID.20231005.Iter200:33  \n",
       "cGEP51  UKCOVID.20231005.Iter200:36  \n",
       "cGEP52  UKCOVID.20231005.Iter200:41  \n",
       "cGEP53  UKCOVID.20231005.Iter200:42  \n",
       "cGEP54  UKCOVID.20231005.Iter200:43  \n",
       "cGEP55  UKCOVID.20231005.Iter200:44  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clus_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d72b45fb-657d-469f-81bf-95ad847b0c51",
   "metadata": {},
   "source": [
    "# Look at top genes of merged GEPs "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bcc33026-69f1-444f-a054-ee12db226898",
   "metadata": {},
   "source": [
    "To help with interpretation of the top genes associated with each cGEP and the genes that were merged together, we output the ```top_genes``` dict variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9f8bd167-9d2c-4aaa-9a30-7253a22135e8",
   "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>COMBAT.20230927.Iter200</th>\n",
       "      <th>UKCOVID.20231005.Iter200</th>\n",
       "      <th>cGEP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AB_HLA-DR</td>\n",
       "      <td>HLA-DRA</td>\n",
       "      <td>HLA-DRA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HLA-DRA</td>\n",
       "      <td>HLA-DRB1</td>\n",
       "      <td>HLA-DRB1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>HLA-DRB5</td>\n",
       "      <td>CD74</td>\n",
       "      <td>CD74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CD74</td>\n",
       "      <td>HLA-DRB5</td>\n",
       "      <td>HLA-DRB5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>HLA-DRB1</td>\n",
       "      <td>HLA-DQB1</td>\n",
       "      <td>HLA-DQB1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>HLA-DQA1</td>\n",
       "      <td>HLA-DQA1</td>\n",
       "      <td>HLA-DQA1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>HLA-DPA1</td>\n",
       "      <td>HLA-DPA1</td>\n",
       "      <td>HLA-DPA1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>HLA-DQB1</td>\n",
       "      <td>HLA-DMA</td>\n",
       "      <td>HLA-DMA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>HLA-DMA</td>\n",
       "      <td>HLA-DPB1</td>\n",
       "      <td>HLA-DPB1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>HLA-DPB1</td>\n",
       "      <td>AB_HLA-DR</td>\n",
       "      <td>HLA-DQA2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   COMBAT.20230927.Iter200 UKCOVID.20231005.Iter200      cGEP\n",
       "1                AB_HLA-DR                  HLA-DRA   HLA-DRA\n",
       "2                  HLA-DRA                 HLA-DRB1  HLA-DRB1\n",
       "3                 HLA-DRB5                     CD74      CD74\n",
       "4                     CD74                 HLA-DRB5  HLA-DRB5\n",
       "5                 HLA-DRB1                 HLA-DQB1  HLA-DQB1\n",
       "6                 HLA-DQA1                 HLA-DQA1  HLA-DQA1\n",
       "7                 HLA-DPA1                 HLA-DPA1  HLA-DPA1\n",
       "8                 HLA-DQB1                  HLA-DMA   HLA-DMA\n",
       "9                  HLA-DMA                 HLA-DPB1  HLA-DPB1\n",
       "10                HLA-DPB1                AB_HLA-DR  HLA-DQA2"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_genes['cGEP1'].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7ea28d57-c511-4326-9c3a-5bc6ac8e0363",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>COMBAT.20230927.Iter200</th>\n",
       "      <th>HIVVaccine.20230907.Iter200</th>\n",
       "      <th>UKCOVID.20231005.Iter200</th>\n",
       "      <th>cGEP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MT-CYB</td>\n",
       "      <td>MT-ATP6</td>\n",
       "      <td>MT-CO2</td>\n",
       "      <td>MT-CO2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MT-ATP6</td>\n",
       "      <td>MT-CYB</td>\n",
       "      <td>MT-CYB</td>\n",
       "      <td>MT-CYB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MT-CO3</td>\n",
       "      <td>MT-CO2</td>\n",
       "      <td>MT-CO3</td>\n",
       "      <td>MT-ATP6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MT-ND4L</td>\n",
       "      <td>MT-ND4</td>\n",
       "      <td>MT-ND4</td>\n",
       "      <td>MT-CO3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>MT-CO2</td>\n",
       "      <td>MT-CO3</td>\n",
       "      <td>MT-ATP6</td>\n",
       "      <td>MT-ND4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>MT-ND5</td>\n",
       "      <td>MT-ND3</td>\n",
       "      <td>MT-CO1</td>\n",
       "      <td>MT-ND3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>MT-ATP8</td>\n",
       "      <td>MT-ND2</td>\n",
       "      <td>MT-ND3</td>\n",
       "      <td>MT-ND5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>MT-CO1</td>\n",
       "      <td>MT-ND1</td>\n",
       "      <td>MT-ND4L</td>\n",
       "      <td>MT-CO1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>MT-ND3</td>\n",
       "      <td>MT-ND5</td>\n",
       "      <td>MT-ND5</td>\n",
       "      <td>MT-ND2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>MT-ND4</td>\n",
       "      <td>MT-CO1</td>\n",
       "      <td>MT-ND1</td>\n",
       "      <td>MT-ND1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   COMBAT.20230927.Iter200 HIVVaccine.20230907.Iter200  \\\n",
       "1                   MT-CYB                     MT-ATP6   \n",
       "2                  MT-ATP6                      MT-CYB   \n",
       "3                   MT-CO3                      MT-CO2   \n",
       "4                  MT-ND4L                      MT-ND4   \n",
       "5                   MT-CO2                      MT-CO3   \n",
       "6                   MT-ND5                      MT-ND3   \n",
       "7                  MT-ATP8                      MT-ND2   \n",
       "8                   MT-CO1                      MT-ND1   \n",
       "9                   MT-ND3                      MT-ND5   \n",
       "10                  MT-ND4                      MT-CO1   \n",
       "\n",
       "   UKCOVID.20231005.Iter200     cGEP  \n",
       "1                    MT-CO2   MT-CO2  \n",
       "2                    MT-CYB   MT-CYB  \n",
       "3                    MT-CO3  MT-ATP6  \n",
       "4                    MT-ND4   MT-CO3  \n",
       "5                   MT-ATP6   MT-ND4  \n",
       "6                    MT-CO1   MT-ND3  \n",
       "7                    MT-ND3   MT-ND5  \n",
       "8                   MT-ND4L   MT-CO1  \n",
       "9                    MT-ND5   MT-ND2  \n",
       "10                   MT-ND1   MT-ND1  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_genes['cGEP2'].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3769f6d7-d0af-47c9-9c00-bbcc1b0dee53",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>COMBAT.20230927.Iter200</th>\n",
       "      <th>HIVVaccine.20230907.Iter200</th>\n",
       "      <th>UKCOVID.20231005.Iter200</th>\n",
       "      <th>cGEP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MX1</td>\n",
       "      <td>ISG15</td>\n",
       "      <td>ISG15</td>\n",
       "      <td>ISG15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ISG15</td>\n",
       "      <td>MX1</td>\n",
       "      <td>MX1</td>\n",
       "      <td>MX1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>IFIT3</td>\n",
       "      <td>IFI6</td>\n",
       "      <td>IFI6</td>\n",
       "      <td>IFI6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>IFIT1</td>\n",
       "      <td>IFI44L</td>\n",
       "      <td>IFIT3</td>\n",
       "      <td>IFIT3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>IFI6</td>\n",
       "      <td>IFIT3</td>\n",
       "      <td>OAS1</td>\n",
       "      <td>IFI44L</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>OAS1</td>\n",
       "      <td>IFIT1</td>\n",
       "      <td>IFIT1</td>\n",
       "      <td>IFIT1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>RSAD2</td>\n",
       "      <td>XAF1</td>\n",
       "      <td>RSAD2</td>\n",
       "      <td>OAS1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>IFI44L</td>\n",
       "      <td>RSAD2</td>\n",
       "      <td>IFI44L</td>\n",
       "      <td>RSAD2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>LY6E</td>\n",
       "      <td>EIF2AK2</td>\n",
       "      <td>IRF7</td>\n",
       "      <td>XAF1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>IFITM1</td>\n",
       "      <td>STAT1</td>\n",
       "      <td>CMPK2</td>\n",
       "      <td>STAT1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   COMBAT.20230927.Iter200 HIVVaccine.20230907.Iter200  \\\n",
       "1                      MX1                       ISG15   \n",
       "2                    ISG15                         MX1   \n",
       "3                    IFIT3                        IFI6   \n",
       "4                    IFIT1                      IFI44L   \n",
       "5                     IFI6                       IFIT3   \n",
       "6                     OAS1                       IFIT1   \n",
       "7                    RSAD2                        XAF1   \n",
       "8                   IFI44L                       RSAD2   \n",
       "9                     LY6E                     EIF2AK2   \n",
       "10                  IFITM1                       STAT1   \n",
       "\n",
       "   UKCOVID.20231005.Iter200    cGEP  \n",
       "1                     ISG15   ISG15  \n",
       "2                       MX1     MX1  \n",
       "3                      IFI6    IFI6  \n",
       "4                     IFIT3   IFIT3  \n",
       "5                      OAS1  IFI44L  \n",
       "6                     IFIT1   IFIT1  \n",
       "7                     RSAD2    OAS1  \n",
       "8                    IFI44L   RSAD2  \n",
       "9                      IRF7    XAF1  \n",
       "10                    CMPK2   STAT1  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_genes['cGEP3'].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "1ac0ff06-b58c-489d-8403-f49a5b21fa29",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>COMBAT.20230927.Iter200</th>\n",
       "      <th>HIVVaccine.20230907.Iter200</th>\n",
       "      <th>UKCOVID.20231005.Iter200</th>\n",
       "      <th>cGEP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TRDV2</td>\n",
       "      <td>TRDC</td>\n",
       "      <td>TRDV2</td>\n",
       "      <td>TRDV2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TRGV9</td>\n",
       "      <td>TRDV2</td>\n",
       "      <td>TRGV9</td>\n",
       "      <td>TRDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AB_TCR-Vd2</td>\n",
       "      <td>TRGC1</td>\n",
       "      <td>TRDC</td>\n",
       "      <td>TRGV9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TRDC</td>\n",
       "      <td>AB_TCR-Vd2</td>\n",
       "      <td>AB_TCR-Vd2</td>\n",
       "      <td>KLRC1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>AB_CD94</td>\n",
       "      <td>KLRC1</td>\n",
       "      <td>KLRC1</td>\n",
       "      <td>TRGC1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>KLRC1</td>\n",
       "      <td>AB_CD3-1</td>\n",
       "      <td>TRGC1</td>\n",
       "      <td>ZBTB16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>AB_TCR-V-9</td>\n",
       "      <td>TRGV9</td>\n",
       "      <td>AB_CD94</td>\n",
       "      <td>KLRD1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>TRGC1</td>\n",
       "      <td>AB_TCR-V-9</td>\n",
       "      <td>ZBTB16</td>\n",
       "      <td>KLRG1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>AB_CD3-1</td>\n",
       "      <td>AB_CD3-2</td>\n",
       "      <td>AB_TCR-V-9</td>\n",
       "      <td>IL18RAP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>AB_KLRG1_MAFA</td>\n",
       "      <td>AB_CD226-1</td>\n",
       "      <td>KLRB1</td>\n",
       "      <td>HOPX</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   COMBAT.20230927.Iter200 HIVVaccine.20230907.Iter200  \\\n",
       "1                    TRDV2                        TRDC   \n",
       "2                    TRGV9                       TRDV2   \n",
       "3               AB_TCR-Vd2                       TRGC1   \n",
       "4                     TRDC                  AB_TCR-Vd2   \n",
       "5                  AB_CD94                       KLRC1   \n",
       "6                    KLRC1                    AB_CD3-1   \n",
       "7               AB_TCR-V-9                       TRGV9   \n",
       "8                    TRGC1                  AB_TCR-V-9   \n",
       "9                 AB_CD3-1                    AB_CD3-2   \n",
       "10           AB_KLRG1_MAFA                  AB_CD226-1   \n",
       "\n",
       "   UKCOVID.20231005.Iter200     cGEP  \n",
       "1                     TRDV2    TRDV2  \n",
       "2                     TRGV9     TRDC  \n",
       "3                      TRDC    TRGV9  \n",
       "4                AB_TCR-Vd2    KLRC1  \n",
       "5                     KLRC1    TRGC1  \n",
       "6                     TRGC1   ZBTB16  \n",
       "7                   AB_CD94    KLRD1  \n",
       "8                    ZBTB16    KLRG1  \n",
       "9                AB_TCR-V-9  IL18RAP  \n",
       "10                    KLRB1     HOPX  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_genes['cGEP4'].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "df0074b9-e9cc-4fca-ad34-9cad934fe522",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>COMBAT.20230927.Iter200</th>\n",
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       "      <th>UKCOVID.20231005.Iter200</th>\n",
       "      <th>cGEP</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FOXP3</td>\n",
       "      <td>FOXP3</td>\n",
       "      <td>FOXP3</td>\n",
       "      <td>FOXP3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AB_CD25</td>\n",
       "      <td>AB_CD25</td>\n",
       "      <td>RTKN2</td>\n",
       "      <td>RTKN2</td>\n",
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       "      <th>3</th>\n",
       "      <td>AB_CD39</td>\n",
       "      <td>RTKN2</td>\n",
       "      <td>IL2RA</td>\n",
       "      <td>IL2RA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RTKN2</td>\n",
       "      <td>IL2RA</td>\n",
       "      <td>FANK1</td>\n",
       "      <td>FANK1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>AB_CD95</td>\n",
       "      <td>FANK1</td>\n",
       "      <td>CTLA4</td>\n",
       "      <td>TIGIT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>IL2RA</td>\n",
       "      <td>TIGIT</td>\n",
       "      <td>STAM</td>\n",
       "      <td>IKZF2</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>FANK1</td>\n",
       "      <td>ICA1</td>\n",
       "      <td>IKZF2</td>\n",
       "      <td>CTLA4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>AB_CD194</td>\n",
       "      <td>CLNK</td>\n",
       "      <td>HACD1</td>\n",
       "      <td>ICA1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>HPGD</td>\n",
       "      <td>RBMS3</td>\n",
       "      <td>AB_CD25</td>\n",
       "      <td>STAM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>IL32</td>\n",
       "      <td>IKZF2</td>\n",
       "      <td>AB_CD39</td>\n",
       "      <td>HACD1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   COMBAT.20230927.Iter200 HIVVaccine.20230907.Iter200  \\\n",
       "1                    FOXP3                       FOXP3   \n",
       "2                  AB_CD25                     AB_CD25   \n",
       "3                  AB_CD39                       RTKN2   \n",
       "4                    RTKN2                       IL2RA   \n",
       "5                  AB_CD95                       FANK1   \n",
       "6                    IL2RA                       TIGIT   \n",
       "7                    FANK1                        ICA1   \n",
       "8                 AB_CD194                        CLNK   \n",
       "9                     HPGD                       RBMS3   \n",
       "10                    IL32                       IKZF2   \n",
       "\n",
       "   UKCOVID.20231005.Iter200   cGEP  \n",
       "1                     FOXP3  FOXP3  \n",
       "2                     RTKN2  RTKN2  \n",
       "3                     IL2RA  IL2RA  \n",
       "4                     FANK1  FANK1  \n",
       "5                     CTLA4  TIGIT  \n",
       "6                      STAM  IKZF2  \n",
       "7                     IKZF2  CTLA4  \n",
       "8                     HACD1   ICA1  \n",
       "9                   AB_CD25   STAM  \n",
       "10                  AB_CD39  HACD1  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_genes['cGEP7'].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "697e37d0-2819-4509-993c-426907418631",
   "metadata": {},
   "source": [
    "Looking at the top genes for several cGEPs above, we see excellent concordance of the merged programs corresponding to HLA, mitochondria,  interferon stimulated genes, gamma delta T-cells, and Tregs respectively"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05b01995-8fea-4e35-96d2-a3bef9097243",
   "metadata": {},
   "source": [
    "# Finally we illustrate running starCAT using the created reference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6f04e09b-e1b8-49e7-877e-f208012da99f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# load query data\n",
    "query_adata = sc.read('./Example_refbuilder/example_memoryT_query.h5ad')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "8cf678c7-9756-46e6-9f5e-037e2b951302",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 1500 × 11362\n",
       "    obs: 'cell_id', 'nUMI', 'nGene', 'percent_mito', 'batch', 'TB_status', 'UMAP_1', 'UMAP_2', 'cluster_name', 'cluster_ids', 'donor', 'gdT_4_Usage', 'ISG_3_Usage', 'HLA_1_Usage'\n",
       "    var: 'Name', 'Name_ADT_Fixed', 'Gene_ADT_Fixed', 'Clone_ADT_Fixed', 'feature_types', 'n_cells'\n",
       "    obsm: 'X_umap'"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query_adata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "415fdc44-b257-41ef-9cc8-174383dc04c9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using user specified reference spectra file ./Example_refbuilder/starcat_refstarcat_consensus_spectra_normalized.filtered.txt\n",
      "No scores provided\n"
     ]
    }
   ],
   "source": [
    "custom_tcat = starCAT(reference='./Example_refbuilder/starcat_refstarcat_consensus_spectra_normalized.filtered.txt', \n",
    "               cachedir='./Example_refbuilder/starcat_cache')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "020ba4c7-3e9e-452e-ae7d-0a8f3274cb25",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2093 out of 3093 genes in the reference overlap with the query\n"
     ]
    }
   ],
   "source": [
    "usage, _ = custom_tcat.fit_transform(query_adata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1d6e484a-650b-44dc-b4cc-b4ceee5eca5c",
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cGEP1</th>\n",
       "      <th>cGEP2</th>\n",
       "      <th>cGEP3</th>\n",
       "      <th>cGEP4</th>\n",
       "      <th>cGEP5</th>\n",
       "      <th>cGEP6</th>\n",
       "      <th>cGEP7</th>\n",
       "      <th>cGEP8</th>\n",
       "      <th>cGEP9</th>\n",
       "      <th>cGEP10</th>\n",
       "      <th>...</th>\n",
       "      <th>cGEP24</th>\n",
       "      <th>cGEP25</th>\n",
       "      <th>cGEP26</th>\n",
       "      <th>cGEP27</th>\n",
       "      <th>cGEP28</th>\n",
       "      <th>cGEP29</th>\n",
       "      <th>cGEP30</th>\n",
       "      <th>cGEP31</th>\n",
       "      <th>cGEP32</th>\n",
       "      <th>cGEP33</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAACCCAAGGCCTAAG-1</th>\n",
       "      <td>0.000313</td>\n",
       "      <td>0.048632</td>\n",
       "      <td>0.008491</td>\n",
       "      <td>0.003332</td>\n",
       "      <td>0.000928</td>\n",
       "      <td>0.002163</td>\n",
       "      <td>0.035945</td>\n",
       "      <td>0.087533</td>\n",
       "      <td>0.003413</td>\n",
       "      <td>0.025892</td>\n",
       "      <td>...</td>\n",
       "      <td>0.049486</td>\n",
       "      <td>0.000650</td>\n",
       "      <td>0.035107</td>\n",
       "      <td>0.094742</td>\n",
       "      <td>0.004896</td>\n",
       "      <td>0.020635</td>\n",
       "      <td>0.156097</td>\n",
       "      <td>0.000889</td>\n",
       "      <td>0.016670</td>\n",
       "      <td>0.003557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACCCAAGGTTCTTG-1</th>\n",
       "      <td>0.000279</td>\n",
       "      <td>0.069953</td>\n",
       "      <td>0.004965</td>\n",
       "      <td>0.002893</td>\n",
       "      <td>0.000838</td>\n",
       "      <td>0.002300</td>\n",
       "      <td>0.032320</td>\n",
       "      <td>0.050753</td>\n",
       "      <td>0.005992</td>\n",
       "      <td>0.030862</td>\n",
       "      <td>...</td>\n",
       "      <td>0.048995</td>\n",
       "      <td>0.001049</td>\n",
       "      <td>0.049087</td>\n",
       "      <td>0.028034</td>\n",
       "      <td>0.012477</td>\n",
       "      <td>0.072036</td>\n",
       "      <td>0.168531</td>\n",
       "      <td>0.002944</td>\n",
       "      <td>0.008421</td>\n",
       "      <td>0.010008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACCCAAGTGCAGGT-1</th>\n",
       "      <td>0.000966</td>\n",
       "      <td>0.108113</td>\n",
       "      <td>0.005859</td>\n",
       "      <td>0.002994</td>\n",
       "      <td>0.004012</td>\n",
       "      <td>0.004082</td>\n",
       "      <td>0.279751</td>\n",
       "      <td>0.014692</td>\n",
       "      <td>0.004408</td>\n",
       "      <td>0.033080</td>\n",
       "      <td>...</td>\n",
       "      <td>0.017157</td>\n",
       "      <td>0.003782</td>\n",
       "      <td>0.021309</td>\n",
       "      <td>0.027117</td>\n",
       "      <td>0.024439</td>\n",
       "      <td>0.003597</td>\n",
       "      <td>0.108805</td>\n",
       "      <td>0.002703</td>\n",
       "      <td>0.003619</td>\n",
       "      <td>0.004182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACCCACAAGAGTAT-1</th>\n",
       "      <td>0.001393</td>\n",
       "      <td>0.056597</td>\n",
       "      <td>0.001030</td>\n",
       "      <td>0.003184</td>\n",
       "      <td>0.002282</td>\n",
       "      <td>0.006199</td>\n",
       "      <td>0.070077</td>\n",
       "      <td>0.154062</td>\n",
       "      <td>0.040958</td>\n",
       "      <td>0.045198</td>\n",
       "      <td>...</td>\n",
       "      <td>0.038374</td>\n",
       "      <td>0.004035</td>\n",
       "      <td>0.036568</td>\n",
       "      <td>0.032168</td>\n",
       "      <td>0.046441</td>\n",
       "      <td>0.013584</td>\n",
       "      <td>0.150373</td>\n",
       "      <td>0.001098</td>\n",
       "      <td>0.006997</td>\n",
       "      <td>0.011473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAACCCACACACGGTC-1</th>\n",
       "      <td>0.001958</td>\n",
       "      <td>0.019257</td>\n",
       "      <td>0.006936</td>\n",
       "      <td>0.012292</td>\n",
       "      <td>0.001546</td>\n",
       "      <td>0.027322</td>\n",
       "      <td>0.022442</td>\n",
       "      <td>0.093716</td>\n",
       "      <td>0.033535</td>\n",
       "      <td>0.032821</td>\n",
       "      <td>...</td>\n",
       "      <td>0.010966</td>\n",
       "      <td>0.005829</td>\n",
       "      <td>0.027569</td>\n",
       "      <td>0.078685</td>\n",
       "      <td>0.018620</td>\n",
       "      <td>0.017401</td>\n",
       "      <td>0.012230</td>\n",
       "      <td>0.002229</td>\n",
       "      <td>0.108355</td>\n",
       "      <td>0.009363</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 33 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       cGEP1     cGEP2     cGEP3     cGEP4     cGEP5  \\\n",
       "AAACCCAAGGCCTAAG-1  0.000313  0.048632  0.008491  0.003332  0.000928   \n",
       "AAACCCAAGGTTCTTG-1  0.000279  0.069953  0.004965  0.002893  0.000838   \n",
       "AAACCCAAGTGCAGGT-1  0.000966  0.108113  0.005859  0.002994  0.004012   \n",
       "AAACCCACAAGAGTAT-1  0.001393  0.056597  0.001030  0.003184  0.002282   \n",
       "AAACCCACACACGGTC-1  0.001958  0.019257  0.006936  0.012292  0.001546   \n",
       "\n",
       "                       cGEP6     cGEP7     cGEP8     cGEP9    cGEP10  ...  \\\n",
       "AAACCCAAGGCCTAAG-1  0.002163  0.035945  0.087533  0.003413  0.025892  ...   \n",
       "AAACCCAAGGTTCTTG-1  0.002300  0.032320  0.050753  0.005992  0.030862  ...   \n",
       "AAACCCAAGTGCAGGT-1  0.004082  0.279751  0.014692  0.004408  0.033080  ...   \n",
       "AAACCCACAAGAGTAT-1  0.006199  0.070077  0.154062  0.040958  0.045198  ...   \n",
       "AAACCCACACACGGTC-1  0.027322  0.022442  0.093716  0.033535  0.032821  ...   \n",
       "\n",
       "                      cGEP24    cGEP25    cGEP26    cGEP27    cGEP28  \\\n",
       "AAACCCAAGGCCTAAG-1  0.049486  0.000650  0.035107  0.094742  0.004896   \n",
       "AAACCCAAGGTTCTTG-1  0.048995  0.001049  0.049087  0.028034  0.012477   \n",
       "AAACCCAAGTGCAGGT-1  0.017157  0.003782  0.021309  0.027117  0.024439   \n",
       "AAACCCACAAGAGTAT-1  0.038374  0.004035  0.036568  0.032168  0.046441   \n",
       "AAACCCACACACGGTC-1  0.010966  0.005829  0.027569  0.078685  0.018620   \n",
       "\n",
       "                      cGEP29    cGEP30    cGEP31    cGEP32    cGEP33  \n",
       "AAACCCAAGGCCTAAG-1  0.020635  0.156097  0.000889  0.016670  0.003557  \n",
       "AAACCCAAGGTTCTTG-1  0.072036  0.168531  0.002944  0.008421  0.010008  \n",
       "AAACCCAAGTGCAGGT-1  0.003597  0.108805  0.002703  0.003619  0.004182  \n",
       "AAACCCACAAGAGTAT-1  0.013584  0.150373  0.001098  0.006997  0.011473  \n",
       "AAACCCACACACGGTC-1  0.017401  0.012230  0.002229  0.108355  0.009363  \n",
       "\n",
       "[5 rows x 33 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "usage.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dcf88364-9eaf-4860-b9d6-9dee28c5d20f",
   "metadata": {},
   "source": [
    "# We can now visualize the usage of our custome cGEP reference. Lets take a look at the gdT signal (cGEP4) and the Treg signal (cGEP7) on the UMAP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "879aeffa-e096-41f0-bdc1-ab44de70c360",
   "metadata": {},
   "outputs": [],
   "source": [
    "query_adata.obs['gdT_4_Usage'] = usage['cGEP4']\n",
    "query_adata.obs['ISG_3_Usage'] = usage['cGEP3']\n",
    "query_adata.obs['HLA_1_Usage'] = usage['cGEP1']\n",
    "query_adata.obs['Treg_7_Usage'] = usage['cGEP7']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "350468bc-98c9-4c8b-8b05-ba9b7ff8b4d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1455.6x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sc.pl.umap(query_adata, color=['gdT_4_Usage', 'Treg_7_Usage'], vmax='p99')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f145b1d5-cb27-4b50-9f60-1c0a45dd9874",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.8.19"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}