{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "091be986-ff7a-4697-9c5a-7f8094642cda",
   "metadata": {},
   "source": [
    "# Minimal example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "18bcf460-6d87-487c-8433-7fa9f898970a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import circe as ci\n",
    "import scanpy as sc\n",
    "import scipy as sp"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56049b45",
   "metadata": {},
   "source": [
    "## Import (or create) data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3972a885-0c5c-4378-81c2-26b7cfdee1f6",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Creating fake AnnData"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d0ec88e-0410-4e5c-a2d1-beb196b02b16",
   "metadata": {},
   "source": [
    "This data doesn't contain strong correlation between fake regions, the score will then be low. \n",
    "\n",
    "It will still allow us to demonstrate how to use Circe. :)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "79295862-9df3-4fa4-a32c-0931c73c705f",
   "metadata": {},
   "outputs": [],
   "source": [
    "atac = sc.datasets.blobs(n_centers=8, n_variables=2_000, n_observations=300, random_state=1)\n",
    "atac.X = np.random.poisson(lam=0.2, size=atac.X.shape)\n",
    "cell_names = [f\"cell_{i}\" for i in range(1, atac.shape[0]+1)]\n",
    "# number of chr_start_end region names\n",
    "region_names = [[f\"chr{i}_{str(j)}_{str(j+399)}\" \n",
    "                 for j in range(1, 10000*400+1, 10000)] \n",
    "                for i in range(1, 6)]\n",
    "regions_names = [item for sublist in region_names for item in sublist]\n",
    "# select a random number of regions per cell, and make it 0\n",
    "for i in range(atac.shape[0]):\n",
    "    num_regions = np.random.randint(500, 1000)\n",
    "    region_indices = np.random.choice(len(regions_names), num_regions, replace=False)\n",
    "    atac.X[i, region_indices] = 0\n",
    "\n",
    "atac.var_names = regions_names\n",
    "atac.obs_names = cell_names"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f4fbec1",
   "metadata": {},
   "source": [
    "## 1. Preprocessing the data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50a80d79-8423-473a-9810-6dc35b7e9900",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### 1.1. Filtering the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "30d98f97-b3b5-4d21-ae8f-4de6c9797f29",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "sc.pp.filter_genes(atac, min_cells=30)\n",
    "sc.pp.filter_cells(atac, min_genes=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e52b2c18",
   "metadata": {},
   "source": [
    "_Make sure to all your features (peaks) are expressed in at least 1 of the cells:_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "af47d8e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.pp.filter_genes(atac, min_counts=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56bbfdba-4447-4778-b4d7-83be18c8923f",
   "metadata": {
    "tags": []
   },
   "source": [
    "### 1.2. Adding region position in AnnData.obs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42c7fb90-ff33-4058-b1a0-aaf99ef0719f",
   "metadata": {},
   "source": [
    "Let's first run `add_region_infos` that will <font color=#F98128>**add coordinate annotations**</font> `chr`, `start`, `end` as columns in `atac.var` slot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2feb1282-0e2b-4e10-bb8b-8f448e4ca2a6",
   "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>n_cells</th>\n",
       "      <th>n_counts</th>\n",
       "      <th>chromosome</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>chr1_1_400</th>\n",
       "      <td>34</td>\n",
       "      <td>38</td>\n",
       "      <td>chr1</td>\n",
       "      <td>1</td>\n",
       "      <td>400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chr1_10001_10400</th>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>chr1</td>\n",
       "      <td>10001</td>\n",
       "      <td>10400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chr1_20001_20400</th>\n",
       "      <td>34</td>\n",
       "      <td>36</td>\n",
       "      <td>chr1</td>\n",
       "      <td>20001</td>\n",
       "      <td>20400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  n_cells  n_counts chromosome  start    end\n",
       "chr1_1_400             34        38       chr1      1    400\n",
       "chr1_10001_10400       31        31       chr1  10001  10400\n",
       "chr1_20001_20400       34        36       chr1  20001  20400"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "atac = ci.add_region_infos(atac)\n",
    "atac.var.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d5c7a34-66cc-4587-b8d5-e485dc975fd8",
   "metadata": {
    "tags": []
   },
   "source": [
    "### 2. Computing pseudocells"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b38f6946-9c5d-4462-be04-04a930dc5bd2",
   "metadata": {},
   "source": [
    "<font color=#F98128>**Compute metacells**</font> is an interesting step to reduce sparsity in our data, since scATAC-seq data have usually a lot of dropouts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2d8f7966-3f9c-4d73-bd67-5bef4fabd53f",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bfd769df251344f48141c7d2ee30269e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "metacells = ci.metacells.compute_metacells(atac)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "85c4ee0a-eab8-4516-b37a-39504615484d",
   "metadata": {},
   "source": [
    "You can also use your own dimensionality reduction space, that would be stored in the atac.obsm slot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "72d6916a-8006-4b98-a5ed-645167dbab79",
   "metadata": {},
   "outputs": [],
   "source": [
    "atac.obsm[\"dim_reduction_name\"] = atac.X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3ca0b58c-6e96-4847-8a42-f79e011df286",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using adata.obsm['dim_reduction_name'] to identify neighboring cells\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "40a350f9b140462b9289791ebb168378",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 300 × 1568\n",
       "    var: 'n_cells', 'n_counts', 'chromosome', 'start', 'end'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ci.metacells.compute_metacells(atac, dim_reduction=\"dim_reduction_name\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23c4e2ef-c346-4c63-9efb-8e4bbeb95cb2",
   "metadata": {},
   "source": [
    "### 3. Calculating co-accessibility"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8cab636-4a10-40cd-a347-5f3e3269f16e",
   "metadata": {},
   "source": [
    "We can finally <font color=#F98128>**compute all the cis co-accessibility scores**</font> ! <br>\n",
    "The default way is to <font color='#50B848'>**indicate your organism**</font> if among the one known by Circe.<br>\n",
    "The atac network is stored automatically as a sparse matrix in `atac.varp[\"atac_network\"]`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "85035bc6-5fa6-4cef-839f-7a9f12926753",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "629efb5ef5d64625a809a2d82492be9e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "14101746ec6e4fb1add5cdd914e6302e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calculating co-accessibility scores...\n",
      "Concatenating results from all chromosomes...\n"
     ]
    }
   ],
   "source": [
    "ci.compute_atac_network(\n",
    "    metacells,\n",
    "    njobs=3, verbose=0,\n",
    "    organism=\"human\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aad0c904-effe-43a0-b504-d12089176550",
   "metadata": {},
   "source": [
    "### 4. Extract connections"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "735f7800-4f9a-4526-853c-d878f031dbf5",
   "metadata": {},
   "source": [
    "#### 4.A.Get the whole genome cis-coaccessible network\n",
    "\n",
    "You can <font color='#F98128'>**extract connections**</font> from the atac.varp slot (sparse matrix), as a `DataFrame object` with `extract_atac_links`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "0a26c332-5a1e-4b10-bf0b-3e6339dace60",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "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>Peak1</th>\n",
       "      <th>Peak2</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1_1480001_1480400</td>\n",
       "      <td>chr1_1540001_1540400</td>\n",
       "      <td>0.377099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr4_1600001_1600400</td>\n",
       "      <td>chr4_1680001_1680400</td>\n",
       "      <td>0.323789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr4_10001_10400</td>\n",
       "      <td>chr4_90001_90400</td>\n",
       "      <td>0.298156</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Peak1                 Peak2     score\n",
       "0  chr1_1480001_1480400  chr1_1540001_1540400  0.377099\n",
       "1  chr4_1600001_1600400  chr4_1680001_1680400  0.323789\n",
       "2      chr4_10001_10400      chr4_90001_90400  0.298156"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circe_network = ci.extract_atac_links(metacells) #atac)\n",
    "circe_network.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07516731-4de2-48c6-bd59-5fcffca34084",
   "metadata": {},
   "source": [
    "#### 4.B. Subset the AnnData object to a given window"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8a1bc5a-dfc0-4437-aed6-2e6606165378",
   "metadata": {},
   "source": [
    "If you're interested in a specific genomic region only, you can also <font color='#F98128'>**subset your anndata object**</font> on this specific window"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f699ad6c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "subset_atac = ci.subset_region(metacells, \"chr1\", 10_000, 200_000).copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "39d41ca4",
   "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>Peak1</th>\n",
       "      <th>Peak2</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr1_70001_70400</td>\n",
       "      <td>chr1_130001_130400</td>\n",
       "      <td>0.092886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr1_60001_60400</td>\n",
       "      <td>chr1_90001_90400</td>\n",
       "      <td>0.000373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr1_100001_100400</td>\n",
       "      <td>chr1_190001_190400</td>\n",
       "      <td>0.000067</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Peak1               Peak2     score\n",
       "0    chr1_70001_70400  chr1_130001_130400  0.092886\n",
       "1    chr1_60001_60400    chr1_90001_90400  0.000373\n",
       "2  chr1_100001_100400  chr1_190001_190400  0.000067"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circe_network_subset = ci.extract_atac_links(subset_atac)\n",
    "circe_network_subset.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c66dcfb-1a1d-4309-bf57-ee9b4ee1f3b4",
   "metadata": {},
   "source": [
    "### 5. Plot co-accessibility scores in a window"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2beae63-65f4-4642-a876-e01a271db740",
   "metadata": {},
   "source": [
    "You can pass either your `anndata` object or your freshly extracted `dataframe` into `plot_connections` to <font color=#F98128>**visualize all Circe scores**</font>.<br>\n",
    "<font color='#4584b6'>**Blue edges**</font> correspond to positive co-accessibility scores, while <font color='#ffde57'>**yellow ones**</font> are for negative scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7e256844-e050-49fc-b811-191b0cf17561",
   "metadata": {},
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 2000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ci.plot_connections(\n",
    "    circe_network,\n",
    "    chromosome=\"chr2\",\n",
    "    start=10_000,\n",
    "    end=200_000,\n",
    "    sep=(\"_\",\"_\"),\n",
    "    abs_threshold=0.01\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46a807ab-4eaa-4951-9f45-eae267bc2ab7",
   "metadata": {},
   "source": [
    "### 7.Coordinates overlap between co-accessible regions and gene bodies"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17d516e3-76b7-454c-b4d5-f8494c549014",
   "metadata": {},
   "source": [
    "To better understand the role of specific regions and modules, you can additionally plot <font color=#F98128>**gene bodies**</font> falling into your window of interest.\n",
    "<br> You need first to load gene coordinates as a dataframe, or to download them through `circe.downloads.download_genes`. This functions will require to install the `pybiomart` package Then you can use `ci.draw.plot_connections_genes`, using gene infos and either your AnnData object or the dataframe of Circe's results to compare these locations. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "4e614cf2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pybiomart in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (0.2.0)\n",
      "Requirement already satisfied: future in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pybiomart) (1.0.0)\n",
      "Requirement already satisfied: pandas in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pybiomart) (2.2.3)\n",
      "Requirement already satisfied: requests in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pybiomart) (2.32.3)\n",
      "Requirement already satisfied: requests-cache in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pybiomart) (1.2.1)\n",
      "Requirement already satisfied: numpy>=1.22.4 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pandas->pybiomart) (1.26.4)\n",
      "Requirement already satisfied: python-dateutil>=2.8.2 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pandas->pybiomart) (2.9.0.post0)\n",
      "Requirement already satisfied: pytz>=2020.1 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pandas->pybiomart) (2025.1)\n",
      "Requirement already satisfied: tzdata>=2022.7 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pandas->pybiomart) (2025.1)\n",
      "Requirement already satisfied: charset_normalizer<4,>=2 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests->pybiomart) (3.4.1)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests->pybiomart) (3.10)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests->pybiomart) (2.2.1)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests->pybiomart) (2024.12.14)\n",
      "Requirement already satisfied: attrs>=21.2 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests-cache->pybiomart) (25.1.0)\n",
      "Requirement already satisfied: cattrs>=22.2 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests-cache->pybiomart) (24.1.2)\n",
      "Requirement already satisfied: platformdirs>=2.5 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests-cache->pybiomart) (4.3.6)\n",
      "Requirement already satisfied: url-normalize>=1.4 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests-cache->pybiomart) (1.4.3)\n",
      "Requirement already satisfied: exceptiongroup>=1.1.1 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from cattrs>=22.2->requests-cache->pybiomart) (1.2.2)\n",
      "Requirement already satisfied: typing-extensions!=4.6.3,>=4.1.0 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from cattrs>=22.2->requests-cache->pybiomart) (4.12.2)\n",
      "Requirement already satisfied: six>=1.5 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from python-dateutil>=2.8.2->pandas->pybiomart) (1.17.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install pybiomart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "0e6fc9fa-98e0-4b95-a95e-92be187a138f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import circe.downloads\n",
    "genes_df = ci.downloads.download_genes()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "094a89c8-8eda-4bae-86cf-cad7a39a276a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 2000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fig, ax = plt.subplots(1, figsize = (20, 6))\n",
    "ci.draw.plot_connections_genes(\n",
    "    connections=metacells,\n",
    "    genes=genes_df,\n",
    "    chromosome=\"chr1\",\n",
    "    start=50_000,\n",
    "    end=350_000,\n",
    "    gene_spacing=30_000,\n",
    "    y_lim_top=-0.01,\n",
    "    abs_threshold=0.0,\n",
    "    track_spacing=0.01,\n",
    "    track_width=0.01,\n",
    "    legend=True,\n",
    "    ax=ax\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af6228fc-9bb2-4fda-9467-b739d8d6a54b",
   "metadata": {},
   "source": [
    "### 7. Work in progress! Happy to get feedbacks :)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79257a67-9d1e-4b22-8dc6-40a95b1b1ede",
   "metadata": {},
   "source": [
    "If you feel any function could be useful for you on others, don't hesitate to write me at `remi.trimbour@pasteur.fr` or to submit an issue on `github.com/cantinilab/Circe`."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "circe_local",
   "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": "3.10.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}