ligrec_benchmark.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "commercial-typing",
   "metadata": {},
   "source": [
    "# Ligrec Benchmark\n",
    "This notebook benchmarks `gr.ligrec` for *squidpy* and *rapids-singlecell*."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "comic-moses",
   "metadata": {},
   "source": [
    "To run this notebook please make sure you have a working rapids environment with all nessaray dependencies. Run the [data_downloader](https://github.com/scverse/rapids_singlecell-notebooks/blob/abc4fc6f3fe7f85cbffb94e76d190cad0ae00a5f/data_downloader.ipynb) notebook first to create the AnnData object we are working with. In this example workflow we'll be looking at a dataset of ca. 90000 cells from [Quin et al., Cell Research 2020](https://www.nature.com/articles/s41422-020-0355-0)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fabulous-ultimate",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import scanpy as sc\n",
    "import squidpy as sq\n",
    "import cupy as cp\n",
    "import rapids_singlecell as rsc\n",
    "\n",
    "import warnings\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "twenty-orbit",
   "metadata": {},
   "outputs": [],
   "source": [
    "import rmm\n",
    "from rmm.allocators.cupy import rmm_cupy_allocator\n",
    "\n",
    "rmm.reinitialize(\n",
    "    managed_memory=False,  # Allows oversubscription\n",
    "    pool_allocator=False,  # default is False\n",
    "    devices=0,  # GPU device IDs to register. By default registers only GPU 0.\n",
    ")\n",
    "cp.cuda.set_allocator(rmm_cupy_allocator)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "scenic-overview",
   "metadata": {},
   "source": [
    "## Load and Prepare Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "saved-plain",
   "metadata": {},
   "source": [
    "We load the sparse count matrix from an `h5ad` file using Scanpy. The sparse count matrix will then be placed on the GPU and run basic preprocessing for `rsc.gr.ligrec`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "comic-fundamental",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2.09 s, sys: 147 ms, total: 2.23 s\n",
      "Wall time: 2.23 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "adata = sc.read(\"h5/adata.raw.h5ad\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "median-excellence",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(93575, 33694)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rsc.get.anndata_to_GPU(adata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "greatest-artwork",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 4.78 ms, sys: 0 ns, total: 4.78 ms\n",
      "Wall time: 4.77 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "rsc.pp.flag_gene_family(adata, gene_family_name=\"MT\", gene_family_prefix=\"MT-\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "weighted-pound",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 82.6 ms, sys: 0 ns, total: 82.6 ms\n",
      "Wall time: 82.2 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "rsc.pp.calculate_qc_metrics(adata, qc_vars=[\"MT\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "729bf0f6-fe0e-4a51-8b54-5921f2d7f7b0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 107 ms, sys: 24.2 ms, total: 131 ms\n",
      "Wall time: 130 ms\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(92666, 33694)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "adata = adata[adata.obs[\"n_genes_by_counts\"] < 5000]\n",
    "adata.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b72750c5-27c7-4c66-b079-db7b0a8c96d3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 9.85 ms, sys: 15.3 ms, total: 25.1 ms\n",
      "Wall time: 24.7 ms\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(91180, 33694)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "adata = adata[adata.obs[\"pct_counts_MT\"] < 20]\n",
    "adata.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "municipal-buyer",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "filtered out 8034 genes based on n_cells_by_counts\n",
      "CPU times: user 64.7 ms, sys: 32.2 ms, total: 96.9 ms\n",
      "Wall time: 96.4 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "rsc.pp.filter_genes(adata, min_count=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "chemical-chair",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.03 ms, sys: 319 µs, total: 1.35 ms\n",
      "Wall time: 863 µs\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "rsc.pp.normalize_total(adata, target_sum=1e4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "confirmed-rainbow",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 0 ns, sys: 7 ms, total: 7 ms\n",
      "Wall time: 6.58 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "rsc.pp.log1p(adata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "falling-soldier",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 121 ms, sys: 36.2 ms, total: 157 ms\n",
      "Wall time: 156 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "rsc.get.anndata_to_CPU(adata)\n",
    "adata.raw = adata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "fa13a7a5-dee0-4b67-a8ee-6e980848ed9f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 91180 × 25660\n",
       "    obs: 'nGene', 'nUMI', 'CellFromTumor', 'PatientNumber', 'TumorType', 'TumorSite', 'CellType', 'n_genes_by_counts', 'total_counts', 'log1p_n_genes_by_counts', 'log1p_total_counts', 'total_counts_MT', 'pct_counts_MT', 'log1p_total_counts_MT'\n",
       "    var: 'gene_ids', 'MT', 'n_cells_by_counts', 'total_counts', 'mean_counts', 'pct_dropout_by_counts', 'log1p_total_counts', 'log1p_mean_counts'\n",
       "    uns: 'log1p'"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a8037c1-5c67-4ec8-9dbe-576e4724ce44",
   "metadata": {},
   "source": [
    "## Ligrec Benchmark\n",
    "\n",
    "First we download the interactions so that both function get evaluated in the same way"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "734a668b-62ac-4ca2-a103-23e538a271c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "interactions = rsc.squidpy_gpu._ligrec._get_interactions()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e41e3a2f-875e-4cd6-bc57-2f511a2ab78f",
   "metadata": {},
   "source": [
    "Next, we execute the function using both the *rapids-singlecell* and *squidpy* versions for comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "804bd797-4650-4e06-94d7-ed6abb965f45",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.45 s, sys: 316 ms, total: 3.77 s\n",
      "Wall time: 3.77 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "res_rsc = rsc.gr.ligrec(\n",
    "    adata,\n",
    "    n_perms=1000,\n",
    "    interactions=interactions,\n",
    "    cluster_key=\"CellType\",\n",
    "    copy=True,\n",
    "    use_raw=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "41712de9-e887-4bb4-a789-a36698b90e96",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>cluster_1</th>\n",
       "      <th colspan=\"10\" halign=\"left\">Alveolar</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>cluster_2</th>\n",
       "      <th>Alveolar</th>\n",
       "      <th>B_cell</th>\n",
       "      <th>Cancer</th>\n",
       "      <th>EC</th>\n",
       "      <th>Epithelial</th>\n",
       "      <th>Erythroblast</th>\n",
       "      <th>Fibroblast</th>\n",
       "      <th>Mast_cell</th>\n",
       "      <th>Myeloid</th>\n",
       "      <th>T_cell</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>source</th>\n",
       "      <th>target</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">EPOR</th>\n",
       "      <th>TRPC3</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.020600</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.020986</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.023505</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.021047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.030588</td>\n",
       "      <td>0.027678</td>\n",
       "      <td>0.027384</td>\n",
       "      <td>0.039786</td>\n",
       "      <td>0.036642</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.042807</td>\n",
       "      <td>0.030903</td>\n",
       "      <td>0.059531</td>\n",
       "      <td>0.033056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FYN</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.021167</td>\n",
       "      <td>0.018256</td>\n",
       "      <td>0.017962</td>\n",
       "      <td>0.030365</td>\n",
       "      <td>0.027220</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.033385</td>\n",
       "      <td>0.021481</td>\n",
       "      <td>0.050110</td>\n",
       "      <td>0.023634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CCL2</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.168153</td>\n",
       "      <td>0.165242</td>\n",
       "      <td>0.164949</td>\n",
       "      <td>0.177351</td>\n",
       "      <td>0.174207</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.180372</td>\n",
       "      <td>0.168468</td>\n",
       "      <td>0.197096</td>\n",
       "      <td>0.170620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KIT</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.013606</td>\n",
       "      <td>0.010695</td>\n",
       "      <td>0.010402</td>\n",
       "      <td>0.022804</td>\n",
       "      <td>0.019660</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.025825</td>\n",
       "      <td>0.013920</td>\n",
       "      <td>0.042549</td>\n",
       "      <td>0.016073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EPO</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.010124</td>\n",
       "      <td>0.007213</td>\n",
       "      <td>0.006920</td>\n",
       "      <td>0.019322</td>\n",
       "      <td>0.016178</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.022343</td>\n",
       "      <td>0.010439</td>\n",
       "      <td>0.039067</td>\n",
       "      <td>0.012591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IFNG</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.018772</td>\n",
       "      <td>0.015861</td>\n",
       "      <td>0.015568</td>\n",
       "      <td>0.027970</td>\n",
       "      <td>0.024826</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.030991</td>\n",
       "      <td>0.019086</td>\n",
       "      <td>0.047715</td>\n",
       "      <td>0.021239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KITLG</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.054305</td>\n",
       "      <td>0.051394</td>\n",
       "      <td>0.051101</td>\n",
       "      <td>0.063503</td>\n",
       "      <td>0.060359</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.066524</td>\n",
       "      <td>0.054620</td>\n",
       "      <td>0.083248</td>\n",
       "      <td>0.056772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NRG1</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.029253</td>\n",
       "      <td>0.026343</td>\n",
       "      <td>0.026049</td>\n",
       "      <td>0.038451</td>\n",
       "      <td>0.035307</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.041472</td>\n",
       "      <td>0.029568</td>\n",
       "      <td>0.058196</td>\n",
       "      <td>0.031721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IL4R</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.053766</td>\n",
       "      <td>0.050856</td>\n",
       "      <td>0.050562</td>\n",
       "      <td>0.062964</td>\n",
       "      <td>0.059820</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.065985</td>\n",
       "      <td>0.054081</td>\n",
       "      <td>0.082709</td>\n",
       "      <td>0.056234</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "cluster_1      Alveolar                                                        \\\n",
       "cluster_2      Alveolar    B_cell    Cancer        EC Epithelial Erythroblast   \n",
       "source target                                                                   \n",
       "EPOR   TRPC3   0.000000  0.020600  0.000000  0.020986   0.000000          0.0   \n",
       "       JAK2    0.030588  0.027678  0.027384  0.039786   0.036642          0.0   \n",
       "FYN    JAK2    0.021167  0.018256  0.017962  0.030365   0.027220          0.0   \n",
       "CCL2   JAK2    0.168153  0.165242  0.164949  0.177351   0.174207          0.0   \n",
       "KIT    JAK2    0.013606  0.010695  0.010402  0.022804   0.019660          0.0   \n",
       "EPO    JAK2    0.010124  0.007213  0.006920  0.019322   0.016178          0.0   \n",
       "IFNG   JAK2    0.018772  0.015861  0.015568  0.027970   0.024826          0.0   \n",
       "KITLG  JAK2    0.054305  0.051394  0.051101  0.063503   0.060359          0.0   \n",
       "NRG1   JAK2    0.029253  0.026343  0.026049  0.038451   0.035307          0.0   \n",
       "IL4R   JAK2    0.053766  0.050856  0.050562  0.062964   0.059820          0.0   \n",
       "\n",
       "cluster_1                                               \n",
       "cluster_2     Fibroblast Mast_cell   Myeloid    T_cell  \n",
       "source target                                           \n",
       "EPOR   TRPC3    0.023505  0.000000  0.000000  0.021047  \n",
       "       JAK2     0.042807  0.030903  0.059531  0.033056  \n",
       "FYN    JAK2     0.033385  0.021481  0.050110  0.023634  \n",
       "CCL2   JAK2     0.180372  0.168468  0.197096  0.170620  \n",
       "KIT    JAK2     0.025825  0.013920  0.042549  0.016073  \n",
       "EPO    JAK2     0.022343  0.010439  0.039067  0.012591  \n",
       "IFNG   JAK2     0.030991  0.019086  0.047715  0.021239  \n",
       "KITLG  JAK2     0.066524  0.054620  0.083248  0.056772  \n",
       "NRG1   JAK2     0.041472  0.029568  0.058196  0.031721  \n",
       "IL4R   JAK2     0.065985  0.054081  0.082709  0.056234  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res_rsc[\"means\"].iloc[:10, :10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "088b6d28-14cf-40e0-a28c-abd9190648f1",
   "metadata": {},
   "outputs": [
    {
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       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>cluster_1</th>\n",
       "      <th colspan=\"10\" halign=\"left\">Alveolar</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>cluster_2</th>\n",
       "      <th>Alveolar</th>\n",
       "      <th>B_cell</th>\n",
       "      <th>Cancer</th>\n",
       "      <th>EC</th>\n",
       "      <th>Epithelial</th>\n",
       "      <th>Erythroblast</th>\n",
       "      <th>Fibroblast</th>\n",
       "      <th>Mast_cell</th>\n",
       "      <th>Myeloid</th>\n",
       "      <th>T_cell</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>source</th>\n",
       "      <th>target</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">EPOR</th>\n",
       "      <th>TRPC3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.516</td>\n",
       "      <td>0.942</td>\n",
       "      <td>0.970</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.164</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.484</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FYN</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CCL2</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KIT</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EPO</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IFNG</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KITLG</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NRG1</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.011</td>\n",
       "      <td>0.079</td>\n",
       "      <td>0.081</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.037</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.071</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IL4R</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.984</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.005</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "cluster_1     Alveolar                                                        \\\n",
       "cluster_2     Alveolar B_cell Cancer   EC Epithelial Erythroblast Fibroblast   \n",
       "source target                                                                  \n",
       "EPOR   TRPC3       NaN    NaN    NaN  NaN        NaN          NaN        NaN   \n",
       "       JAK2      0.516  0.942  0.970  0.0      0.164          NaN      0.000   \n",
       "FYN    JAK2      1.000  1.000  1.000  1.0      1.000          NaN      1.000   \n",
       "CCL2   JAK2      0.000  0.000  0.000  0.0      0.000          NaN      0.000   \n",
       "KIT    JAK2        NaN    NaN    NaN  NaN        NaN          NaN        NaN   \n",
       "EPO    JAK2        NaN    NaN    NaN  NaN        NaN          NaN        NaN   \n",
       "IFNG   JAK2      1.000  1.000  1.000  1.0      1.000          NaN      1.000   \n",
       "KITLG  JAK2      0.000  0.000  0.000  0.0      0.000          NaN      0.000   \n",
       "NRG1   JAK2      0.011  0.079  0.081  0.0      0.037          NaN      0.000   \n",
       "IL4R   JAK2      1.000  1.000  1.000  1.0      0.992          NaN      0.984   \n",
       "\n",
       "cluster_1                               \n",
       "cluster_2     Mast_cell Myeloid T_cell  \n",
       "source target                           \n",
       "EPOR   TRPC3        NaN     NaN    NaN  \n",
       "       JAK2       0.484   0.000  0.074  \n",
       "FYN    JAK2       1.000   1.000  1.000  \n",
       "CCL2   JAK2       0.000   0.000  0.000  \n",
       "KIT    JAK2         NaN     NaN    NaN  \n",
       "EPO    JAK2         NaN     NaN    NaN  \n",
       "IFNG   JAK2       1.000   1.000  1.000  \n",
       "KITLG  JAK2       0.000   0.000  0.000  \n",
       "NRG1   JAK2       0.071   0.000  0.000  \n",
       "IL4R   JAK2       1.000   0.005  1.000  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res_rsc[\"pvalues\"].iloc[:10, :10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "da69b2d8-48a2-447b-9539-f19b4daea711",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a49c3b53e8424d0c8fbdc41030f2b6a7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/1000 [00:00<?, ?permutation/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 20.4 s, sys: 2.02 s, total: 22.5 s\n",
      "Wall time: 52.3 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "res_sq = sq.gr.ligrec(\n",
    "    adata,\n",
    "    n_perms=1000,\n",
    "    interactions=interactions,\n",
    "    cluster_key=\"CellType\",\n",
    "    copy=True,\n",
    "    use_raw=True,\n",
    "    n_jobs=32,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "d9938921-cf0c-4b9c-acd9-90c3eea5caa2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>cluster_1</th>\n",
       "      <th colspan=\"10\" halign=\"left\">Alveolar</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>cluster_2</th>\n",
       "      <th>Alveolar</th>\n",
       "      <th>B_cell</th>\n",
       "      <th>Cancer</th>\n",
       "      <th>EC</th>\n",
       "      <th>Epithelial</th>\n",
       "      <th>Erythroblast</th>\n",
       "      <th>Fibroblast</th>\n",
       "      <th>Mast_cell</th>\n",
       "      <th>Myeloid</th>\n",
       "      <th>T_cell</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>source</th>\n",
       "      <th>target</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">EPOR</th>\n",
       "      <th>TRPC3</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.020600</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.020986</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.023505</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.021047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.030588</td>\n",
       "      <td>0.027678</td>\n",
       "      <td>0.027384</td>\n",
       "      <td>0.039786</td>\n",
       "      <td>0.036642</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.042807</td>\n",
       "      <td>0.030903</td>\n",
       "      <td>0.059531</td>\n",
       "      <td>0.033056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FYN</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.021167</td>\n",
       "      <td>0.018256</td>\n",
       "      <td>0.017962</td>\n",
       "      <td>0.030365</td>\n",
       "      <td>0.027220</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.033385</td>\n",
       "      <td>0.021481</td>\n",
       "      <td>0.050110</td>\n",
       "      <td>0.023634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CCL2</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.168153</td>\n",
       "      <td>0.165242</td>\n",
       "      <td>0.164949</td>\n",
       "      <td>0.177351</td>\n",
       "      <td>0.174207</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.180372</td>\n",
       "      <td>0.168468</td>\n",
       "      <td>0.197096</td>\n",
       "      <td>0.170620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KIT</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.013606</td>\n",
       "      <td>0.010695</td>\n",
       "      <td>0.010402</td>\n",
       "      <td>0.022804</td>\n",
       "      <td>0.019660</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.025825</td>\n",
       "      <td>0.013920</td>\n",
       "      <td>0.042549</td>\n",
       "      <td>0.016073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EPO</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.010124</td>\n",
       "      <td>0.007213</td>\n",
       "      <td>0.006920</td>\n",
       "      <td>0.019322</td>\n",
       "      <td>0.016178</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.022343</td>\n",
       "      <td>0.010439</td>\n",
       "      <td>0.039067</td>\n",
       "      <td>0.012591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IFNG</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.018772</td>\n",
       "      <td>0.015861</td>\n",
       "      <td>0.015568</td>\n",
       "      <td>0.027970</td>\n",
       "      <td>0.024826</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.030991</td>\n",
       "      <td>0.019086</td>\n",
       "      <td>0.047715</td>\n",
       "      <td>0.021239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KITLG</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.054305</td>\n",
       "      <td>0.051394</td>\n",
       "      <td>0.051101</td>\n",
       "      <td>0.063503</td>\n",
       "      <td>0.060359</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.066524</td>\n",
       "      <td>0.054620</td>\n",
       "      <td>0.083248</td>\n",
       "      <td>0.056772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NRG1</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.029253</td>\n",
       "      <td>0.026343</td>\n",
       "      <td>0.026049</td>\n",
       "      <td>0.038451</td>\n",
       "      <td>0.035307</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.041472</td>\n",
       "      <td>0.029568</td>\n",
       "      <td>0.058196</td>\n",
       "      <td>0.031721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IL4R</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.053766</td>\n",
       "      <td>0.050856</td>\n",
       "      <td>0.050562</td>\n",
       "      <td>0.062964</td>\n",
       "      <td>0.059820</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.065985</td>\n",
       "      <td>0.054081</td>\n",
       "      <td>0.082709</td>\n",
       "      <td>0.056234</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "cluster_1      Alveolar                                                        \\\n",
       "cluster_2      Alveolar    B_cell    Cancer        EC Epithelial Erythroblast   \n",
       "source target                                                                   \n",
       "EPOR   TRPC3   0.000000  0.020600  0.000000  0.020986   0.000000          0.0   \n",
       "       JAK2    0.030588  0.027678  0.027384  0.039786   0.036642          0.0   \n",
       "FYN    JAK2    0.021167  0.018256  0.017962  0.030365   0.027220          0.0   \n",
       "CCL2   JAK2    0.168153  0.165242  0.164949  0.177351   0.174207          0.0   \n",
       "KIT    JAK2    0.013606  0.010695  0.010402  0.022804   0.019660          0.0   \n",
       "EPO    JAK2    0.010124  0.007213  0.006920  0.019322   0.016178          0.0   \n",
       "IFNG   JAK2    0.018772  0.015861  0.015568  0.027970   0.024826          0.0   \n",
       "KITLG  JAK2    0.054305  0.051394  0.051101  0.063503   0.060359          0.0   \n",
       "NRG1   JAK2    0.029253  0.026343  0.026049  0.038451   0.035307          0.0   \n",
       "IL4R   JAK2    0.053766  0.050856  0.050562  0.062964   0.059820          0.0   \n",
       "\n",
       "cluster_1                                               \n",
       "cluster_2     Fibroblast Mast_cell   Myeloid    T_cell  \n",
       "source target                                           \n",
       "EPOR   TRPC3    0.023505  0.000000  0.000000  0.021047  \n",
       "       JAK2     0.042807  0.030903  0.059531  0.033056  \n",
       "FYN    JAK2     0.033385  0.021481  0.050110  0.023634  \n",
       "CCL2   JAK2     0.180372  0.168468  0.197096  0.170620  \n",
       "KIT    JAK2     0.025825  0.013920  0.042549  0.016073  \n",
       "EPO    JAK2     0.022343  0.010439  0.039067  0.012591  \n",
       "IFNG   JAK2     0.030991  0.019086  0.047715  0.021239  \n",
       "KITLG  JAK2     0.066524  0.054620  0.083248  0.056772  \n",
       "NRG1   JAK2     0.041472  0.029568  0.058196  0.031721  \n",
       "IL4R   JAK2     0.065985  0.054081  0.082709  0.056234  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res_sq[\"means\"].iloc[:10, :10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "c717fec9-3c00-448c-b46f-92452a90e8f5",
   "metadata": {},
   "outputs": [
    {
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       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>cluster_1</th>\n",
       "      <th colspan=\"10\" halign=\"left\">Alveolar</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>cluster_2</th>\n",
       "      <th>Alveolar</th>\n",
       "      <th>B_cell</th>\n",
       "      <th>Cancer</th>\n",
       "      <th>EC</th>\n",
       "      <th>Epithelial</th>\n",
       "      <th>Erythroblast</th>\n",
       "      <th>Fibroblast</th>\n",
       "      <th>Mast_cell</th>\n",
       "      <th>Myeloid</th>\n",
       "      <th>T_cell</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>source</th>\n",
       "      <th>target</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">EPOR</th>\n",
       "      <th>TRPC3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.497</td>\n",
       "      <td>0.922</td>\n",
       "      <td>0.964</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.135</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.444</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FYN</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CCL2</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KIT</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EPO</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IFNG</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KITLG</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NRG1</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>0.007</td>\n",
       "      <td>0.070</td>\n",
       "      <td>0.080</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.037</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.054</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IL4R</th>\n",
       "      <th>JAK2</th>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.999</td>\n",
       "      <td>0.993</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.977</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.003</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "cluster_1     Alveolar                                               \\\n",
       "cluster_2     Alveolar B_cell Cancer     EC Epithelial Erythroblast   \n",
       "source target                                                         \n",
       "EPOR   TRPC3       NaN    NaN    NaN    NaN        NaN          NaN   \n",
       "       JAK2      0.497  0.922  0.964  0.000      0.135          NaN   \n",
       "FYN    JAK2      1.000  1.000  1.000  1.000      1.000          NaN   \n",
       "CCL2   JAK2      0.000  0.000  0.000  0.000      0.000          NaN   \n",
       "KIT    JAK2        NaN    NaN    NaN    NaN        NaN          NaN   \n",
       "EPO    JAK2        NaN    NaN    NaN    NaN        NaN          NaN   \n",
       "IFNG   JAK2      1.000  1.000  1.000  1.000      1.000          NaN   \n",
       "KITLG  JAK2      0.000  0.000  0.000  0.000      0.000          NaN   \n",
       "NRG1   JAK2      0.007  0.070  0.080  0.000      0.037          NaN   \n",
       "IL4R   JAK2      1.000  1.000  1.000  0.999      0.993          NaN   \n",
       "\n",
       "cluster_1                                          \n",
       "cluster_2     Fibroblast Mast_cell Myeloid T_cell  \n",
       "source target                                      \n",
       "EPOR   TRPC3         NaN       NaN     NaN    NaN  \n",
       "       JAK2        0.000     0.444   0.000   0.06  \n",
       "FYN    JAK2        1.000     1.000   1.000   1.00  \n",
       "CCL2   JAK2        0.000     0.000   0.000   0.00  \n",
       "KIT    JAK2          NaN       NaN     NaN    NaN  \n",
       "EPO    JAK2          NaN       NaN     NaN    NaN  \n",
       "IFNG   JAK2        1.000     1.000   1.000   1.00  \n",
       "KITLG  JAK2        0.000     0.000   0.000   0.00  \n",
       "NRG1   JAK2        0.000     0.054   0.000   0.00  \n",
       "IL4R   JAK2        0.977     1.000   0.003   1.00  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res_sq[\"pvalues\"].iloc[:10, :10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "facd0676-1ec1-44a3-a118-08fdb53327cb",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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