{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simulation analysis\n",
    "\n",
    "This notebook is a minimal example of a simulated perturbation in [CellOracle](https://github.com/morris-lab/CellOracle). Compared to the official docs, there is little new material; rather, we strip down the docs to make them easier to grasp. \n",
    "\n",
    "Read more about CellOracle [here](https://www.biorxiv.org/content/10.1101/2020.02.17.947416v3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/celloracle/trajectory/markov_simulation.py:17: NumbaWarning: \u001b[1m\n",
      "Compilation is falling back to object mode WITH looplifting enabled because Function \"_walk\" failed type inference due to: \u001b[1m\u001b[1m\u001b[1mUndecided type $22load_method.7 := <undecided>\u001b[0m\n",
      "\u001b[0m\u001b[1mDuring: resolving caller type: $22load_method.7\u001b[0m\n",
      "\u001b[0m\u001b[1mDuring: typing of call at /home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/celloracle/trajectory/markov_simulation.py (40)\n",
      "\u001b[0m\n",
      "\u001b[1m\n",
      "File \"../../../../../.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/celloracle/trajectory/markov_simulation.py\", line 40:\u001b[0m\n",
      "\u001b[1mdef _walk(start_cell_id_array, transition_prob, n_steps):\n",
      "    <source elided>\n",
      "\n",
      "\u001b[1m    li.append(list(ids_now))\n",
      "\u001b[0m    \u001b[1m^\u001b[0m\u001b[0m\n",
      "\u001b[0m\n",
      "  @jit(i8[:,:](i8[:], f8[:,:], i8))\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/celloracle/trajectory/markov_simulation.py:17: NumbaWarning: \u001b[1m\n",
      "Compilation is falling back to object mode WITHOUT looplifting enabled because Function \"_walk\" failed type inference due to: \u001b[1m\u001b[1mCannot determine Numba type of <class 'numba.core.dispatcher.LiftedLoop'>\u001b[0m\n",
      "\u001b[1m\n",
      "File \"../../../../../.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/celloracle/trajectory/markov_simulation.py\", line 44:\u001b[0m\n",
      "\u001b[1mdef _walk(start_cell_id_array, transition_prob, n_steps):\n",
      "    <source elided>\n",
      "    # walk for n_steps\n",
      "\u001b[1m    for i in range(n_steps):\n",
      "\u001b[0m    \u001b[1m^\u001b[0m\u001b[0m\n",
      "\u001b[0m\u001b[0m\n",
      "  @jit(i8[:,:](i8[:], f8[:,:], i8))\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/numba/core/object_mode_passes.py:151: NumbaWarning: \u001b[1mFunction \"_walk\" was compiled in object mode without forceobj=True, but has lifted loops.\n",
      "\u001b[1m\n",
      "File \"../../../../../.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/celloracle/trajectory/markov_simulation.py\", line 34:\u001b[0m\n",
      "\u001b[1mdef _walk(start_cell_id_array, transition_prob, n_steps):\n",
      "    <source elided>\n",
      "    \"\"\"\n",
      "\u001b[1m    n_cells = transition_prob.shape[0]\n",
      "\u001b[0m    \u001b[1m^\u001b[0m\u001b[0m\n",
      "\u001b[0m\n",
      "  warnings.warn(errors.NumbaWarning(warn_msg,\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/numba/core/object_mode_passes.py:161: NumbaDeprecationWarning: \u001b[1m\n",
      "Fall-back from the nopython compilation path to the object mode compilation path has been detected, this is deprecated behaviour.\n",
      "\n",
      "For more information visit https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit\n",
      "\u001b[1m\n",
      "File \"../../../../../.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/celloracle/trajectory/markov_simulation.py\", line 34:\u001b[0m\n",
      "\u001b[1mdef _walk(start_cell_id_array, transition_prob, n_steps):\n",
      "    <source elided>\n",
      "    \"\"\"\n",
      "\u001b[1m    n_cells = transition_prob.shape[0]\n",
      "\u001b[0m    \u001b[1m^\u001b[0m\u001b[0m\n",
      "\u001b[0m\n",
      "  warnings.warn(errors.NumbaDeprecationWarning(msg,\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R path: /usr/bin/R\n",
      "Build process aborts.\n",
      "checking_installation: igraph -> NG\n",
      " R library, igraph is unavailable. Please check installation.\n",
      "Build process aborts.\n",
      "checking_installation: linkcomm -> NG\n",
      " R library, linkcomm is unavailable. Please check installation.\n",
      "Build process aborts.\n",
      "checking_installation: rnetcarto -> NG\n",
      " R library, rnetcarto is unavailable. Please check installation.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/celloracle/network_analysis/use_r_scripts.py:75: ResourceWarning: unclosed file <_io.BufferedReader name=44>\n",
      "  print(f\" R library, {i} is unavailable. Please check installation.\")\n",
      "ResourceWarning: Enable tracemalloc to get the object allocation traceback\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/ipykernel/pylab/config.py:79: DeprecationWarning: InlineBackend._figure_format_changed is deprecated in traitlets 4.1: use @observe and @unobserve instead.\n",
      "  def _figure_format_changed(self, name, old, new):\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import sys\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scanpy as sc\n",
    "import seaborn as sns\n",
    "import celloracle as co\n",
    "import warnings\n",
    "warnings.filterwarnings(action='once')\n",
    "\n",
    "co.check_python_requirements()\n",
    "co.test_R_libraries_installation()\n",
    "    \n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "%matplotlib inline\n",
    "plt.rcParams['figure.figsize'] = [6, 4.5]\n",
    "plt.rcParams[\"savefig.dpi\"] = 300\n",
    "save_folder = \"figures\"\n",
    "os.makedirs(save_folder, exist_ok=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We use the example dataset from [Paul et al 2015](https://www.cell.com/cell/pdfExtended/S0092-8674(15)01493-2) and a pre-built default base network derived from motif analysis of ATAC data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
      "  and should_run_async(code)\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/h5ad.py:238: OldFormatWarning: Element '/X' was written without encoding metadata.\n",
      "  d[k] = read_elem(f[k])\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/h5ad.py:238: OldFormatWarning: Element '/layers' was written without encoding metadata.\n",
      "  d[k] = read_elem(f[k])\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/layers/raw_count' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:584: OldFormatWarning: Element '/obs/__categories/paul15_clusters' was written without encoding metadata.\n",
      "  categories = read_elem(categories_dset)\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:587: OldFormatWarning: Element '/obs/paul15_clusters' was written without encoding metadata.\n",
      "  read_elem(dataset), categories, ordered=ordered\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:590: OldFormatWarning: Element '/obs/n_counts_all' was written without encoding metadata.\n",
      "  return read_elem(dataset)\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:590: OldFormatWarning: Element '/obs/n_counts' was written without encoding metadata.\n",
      "  return read_elem(dataset)\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:584: OldFormatWarning: Element '/obs/__categories/louvain' was written without encoding metadata.\n",
      "  categories = read_elem(categories_dset)\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:587: OldFormatWarning: Element '/obs/louvain' was written without encoding metadata.\n",
      "  read_elem(dataset), categories, ordered=ordered\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:584: OldFormatWarning: Element '/obs/__categories/cell_type' was written without encoding metadata.\n",
      "  categories = read_elem(categories_dset)\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:587: OldFormatWarning: Element '/obs/cell_type' was written without encoding metadata.\n",
      "  read_elem(dataset), categories, ordered=ordered\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:584: OldFormatWarning: Element '/obs/__categories/louvain_annot' was written without encoding metadata.\n",
      "  categories = read_elem(categories_dset)\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:587: OldFormatWarning: Element '/obs/louvain_annot' was written without encoding metadata.\n",
      "  read_elem(dataset), categories, ordered=ordered\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:590: OldFormatWarning: Element '/obs/dpt_pseudotime' was written without encoding metadata.\n",
      "  return read_elem(dataset)\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:590: OldFormatWarning: Element '/obs/index' was written without encoding metadata.\n",
      "  return read_elem(dataset)\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/h5ad.py:238: OldFormatWarning: Element '/obsm' was written without encoding metadata.\n",
      "  d[k] = read_elem(f[k])\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/obsm/X_diffmap' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/obsm/X_draw_graph_fa' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/obsm/X_pca' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/h5ad.py:238: OldFormatWarning: Element '/obsp' was written without encoding metadata.\n",
      "  d[k] = read_elem(f[k])\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/h5ad.py:238: OldFormatWarning: Element '/uns' was written without encoding metadata.\n",
      "  d[k] = read_elem(f[k])\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/cell_type_colors' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/diffmap_evals' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/draw_graph' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/draw_graph/params' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/draw_graph/params/layout' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/draw_graph/params/random_state' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/iroot' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/louvain' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/louvain/params' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/louvain/params/random_state' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/louvain/params/resolution' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/louvain_annot_colors' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/louvain_colors' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/louvain_sizes' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/neighbors' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/neighbors/params' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/neighbors/params/method' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/neighbors/params/n_neighbors' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/paga' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/paga/groups' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/paga/pos' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/paul15_clusters_colors' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/pca' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/pca/variance' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/uns/pca/variance_ratio' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:590: OldFormatWarning: Element '/var/n_counts' was written without encoding metadata.\n",
      "  return read_elem(dataset)\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:590: OldFormatWarning: Element '/var/index' was written without encoding metadata.\n",
      "  return read_elem(dataset)\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/h5ad.py:238: OldFormatWarning: Element '/varm' was written without encoding metadata.\n",
      "  d[k] = read_elem(f[k])\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:92: OldFormatWarning: Element '/varm/PCs' was written without encoding metadata.\n",
      "  return {k: read_elem(v) for k, v in elem.items()}\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/h5ad.py:269: OldFormatWarning: Element '/raw/X' was written without encoding metadata.\n",
      "  raw[\"X\"] = read_x(f[\"raw/X\"])\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:590: OldFormatWarning: Element '/raw/var/n_counts' was written without encoding metadata.\n",
      "  return read_elem(dataset)\n",
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/anndata/_io/specs/methods.py:590: OldFormatWarning: Element '/raw/var/index' was written without encoding metadata.\n",
      "  return read_elem(dataset)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>peak_id</th>\n",
       "      <th>gene_short_name</th>\n",
       "      <th>9430076c15rik</th>\n",
       "      <th>Ac002126.6</th>\n",
       "      <th>Ac012531.1</th>\n",
       "      <th>Ac226150.2</th>\n",
       "      <th>Afp</th>\n",
       "      <th>Ahr</th>\n",
       "      <th>Ahrr</th>\n",
       "      <th>Aire</th>\n",
       "      <th>...</th>\n",
       "      <th>Znf784</th>\n",
       "      <th>Znf8</th>\n",
       "      <th>Znf816</th>\n",
       "      <th>Znf85</th>\n",
       "      <th>Zscan10</th>\n",
       "      <th>Zscan16</th>\n",
       "      <th>Zscan22</th>\n",
       "      <th>Zscan26</th>\n",
       "      <th>Zscan31</th>\n",
       "      <th>Zscan4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr10_100050979_100052296</td>\n",
       "      <td>4930430F08Rik</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr10_101006922_101007748</td>\n",
       "      <td>SNORA17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr10_101144061_101145000</td>\n",
       "      <td>Mgat4c</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr10_10148873_10149183</td>\n",
       "      <td>9130014G24Rik</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr10_10149425_10149815</td>\n",
       "      <td>9130014G24Rik</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 1095 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     peak_id gene_short_name  9430076c15rik  Ac002126.6  \\\n",
       "0  chr10_100050979_100052296   4930430F08Rik            0.0         0.0   \n",
       "1  chr10_101006922_101007748         SNORA17            0.0         0.0   \n",
       "2  chr10_101144061_101145000          Mgat4c            0.0         0.0   \n",
       "3    chr10_10148873_10149183   9130014G24Rik            0.0         0.0   \n",
       "4    chr10_10149425_10149815   9130014G24Rik            0.0         0.0   \n",
       "\n",
       "   Ac012531.1  Ac226150.2  Afp  Ahr  Ahrr  Aire  ...  Znf784  Znf8  Znf816  \\\n",
       "0         1.0         0.0  0.0  0.0   0.0   0.0  ...     0.0   0.0     0.0   \n",
       "1         0.0         0.0  0.0  0.0   0.0   0.0  ...     0.0   0.0     0.0   \n",
       "2         0.0         0.0  0.0  0.0   0.0   0.0  ...     0.0   0.0     0.0   \n",
       "3         0.0         0.0  0.0  0.0   0.0   0.0  ...     0.0   0.0     0.0   \n",
       "4         0.0         0.0  0.0  0.0   0.0   0.0  ...     0.0   0.0     0.0   \n",
       "\n",
       "   Znf85  Zscan10  Zscan16  Zscan22  Zscan26  Zscan31  Zscan4  \n",
       "0    0.0      0.0      0.0      0.0      0.0      0.0     0.0  \n",
       "1    0.0      0.0      0.0      0.0      0.0      1.0     0.0  \n",
       "2    0.0      0.0      0.0      0.0      0.0      0.0     1.0  \n",
       "3    0.0      0.0      0.0      0.0      0.0      0.0     0.0  \n",
       "4    0.0      0.0      0.0      0.0      0.0      0.0     0.0  \n",
       "\n",
       "[5 rows x 1095 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata = co.data.load_Paul2015_data()\n",
    "adata.obs[\"fake_cluster\"] = \"all_one_cluster\"\n",
    "base_GRN = co.data.load_mouse_scATAC_atlas_base_GRN()\n",
    "base_GRN.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How to get the expression data and the base network into the CellOracle object. \n",
    "Undo the comments to toggle common errors on and off."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "oracle = co.Oracle()\n",
    "# adata.X = adata.raw.X\n",
    "oracle.import_anndata_as_raw_count(adata=adata,\n",
    "                                   cluster_column_name=\"fake_cluster\", #bad\n",
    "#                                    cluster_column_name=\"louvain_annot\", #good\n",
    "                                   embedding_name=\"X_draw_graph_fa\")\n",
    "oracle.import_TF_data(TF_info_matrix=base_GRN)\n",
    "oracle.addTFinfo_dictionary({\"Foxn1\":['Ccl25', 'Psmb11', 'Pdlim1', 'Mfsd12', 'Mreg', 'Fam57a', 'Ppp1r16b']})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you want to put everything in one cluster, it requires setting certain other undocumented aspects of object state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
      "  and should_run_async(code)\n"
     ]
    }
   ],
   "source": [
    "adata.obs[\"fake_cluster\"]=\"all_one_cluster\"\n",
    "adata.obs.fake_cluster = adata.obs.fake_cluster.astype(\"category\")\n",
    "adata.uns[\"fake_cluster_colors\"] = ['#1f77b4']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then we can train up some models and simulate a knockout. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
      "  and should_run_async(code)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Auto-selected k is :66\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/celloracle/trajectory/neighbors.py:402: DeprecationWarning: Please use `csr_matrix` from the `scipy.sparse` namespace, the `scipy.sparse.csr` namespace is deprecated.\n",
      "  if type(mknn) is not sparse.csr.csr_matrix:\n"
     ]
    }
   ],
   "source": [
    "oracle.perform_PCA()\n",
    "n_comps = 50\n",
    "n_cell = oracle.adata.shape[0]\n",
    "k = int(0.025*n_cell)\n",
    "print(f\"Auto-selected k is :{k}\")\n",
    "oracle.knn_imputation(n_pca_dims=n_comps, k=k, balanced=True, b_sight=k*8,\n",
    "                      b_maxl=k*4, n_jobs=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ekernf01/.local/share/r-miniconda/envs/cscb/lib/python3.9/site-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
      "  and should_run_async(code)\n"
     ]
    },
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     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "inferring GRN for Ery_0...\n"
     ]
    },
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     },
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    },
    {
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     "output_type": "stream",
     "text": [
      "inferring GRN for Ery_1...\n"
     ]
    },
    {
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     "text": [
      "inferring GRN for Ery_2...\n"
     ]
    },
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    {
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     "text": [
      "inferring GRN for Ery_3...\n"
     ]
    },
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    },
    {
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     "output_type": "stream",
     "text": [
      "inferring GRN for Ery_4...\n"
     ]
    },
    {
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "inferring GRN for Ery_5...\n"
     ]
    },
    {
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    },
    {
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     "output_type": "stream",
     "text": [
      "inferring GRN for Ery_6...\n"
     ]
    },
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    },
    {
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     "output_type": "stream",
     "text": [
      "inferring GRN for Ery_7...\n"
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    },
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    {
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     "text": [
      "inferring GRN for Ery_8...\n"
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     "text": [
      "inferring GRN for Ery_9...\n"
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    },
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    {
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     "output_type": "stream",
     "text": [
      "inferring GRN for GMP_0...\n"
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    },
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    {
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     "output_type": "stream",
     "text": [
      "inferring GRN for GMP_1...\n"
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    },
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    },
    {
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     "output_type": "stream",
     "text": [
      "inferring GRN for GMP_2...\n"
     ]
    },
    {
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     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "inferring GRN for GMPl_0...\n"
     ]
    },
    {
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    },
    {
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      "inferring GRN for GMPl_1...\n"
     ]
    },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "inferring GRN for Gran_0...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a5c7061997be4df1a73cdf1b6cedbe3b",
       "version_major": 2,
       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "inferring GRN for Gran_1...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7f875727717f47448ec4843e13db065e",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "inferring GRN for Gran_2...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ca98de6c3a8c4dda92eb6aad4e5c2302",
       "version_major": 2,
       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "inferring GRN for Gran_3...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a259e7263ba643dcb65dbf3ddb8fb6e7",
       "version_major": 2,
       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "inferring GRN for MEP_0...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "88dba37838bd468a811f0a4a1246c51a",
       "version_major": 2,
       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "inferring GRN for Mk_0...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e0095198d2a34c2fa4ab6d8231c1af9a",
       "version_major": 2,
       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "inferring GRN for Mo_0...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "901f9fcce2b9453d8a385b52369b60fd",
       "version_major": 2,
       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "inferring GRN for Mo_1...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "556aeb8978f54d7bae549a49b48ae1ef",
       "version_major": 2,
       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "inferring GRN for Mo_2...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cc2ba3175d0b470bafa53c3f20604b02",
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       "version_minor": 0
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "warnings.filterwarnings('ignore') #Otherwise, np.int nightmare\n",
    "links = oracle.get_links(cluster_name_for_GRN_unit=\"louvain_annot\", alpha=10,\n",
    "                         verbose_level=10, test_mode=False, n_jobs=-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>source</th>\n",
       "      <th>target</th>\n",
       "      <th>coef_mean</th>\n",
       "      <th>coef_abs</th>\n",
       "      <th>p</th>\n",
       "      <th>-logp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mef2c</td>\n",
       "      <td>0610007L01Rik</td>\n",
       "      <td>-0.000324</td>\n",
       "      <td>0.000324</td>\n",
       "      <td>0.741978</td>\n",
       "      <td>0.129609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Gata1</td>\n",
       "      <td>0610007L01Rik</td>\n",
       "      <td>0.002261</td>\n",
       "      <td>0.002261</td>\n",
       "      <td>0.149212</td>\n",
       "      <td>0.826197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Fli1</td>\n",
       "      <td>0610007L01Rik</td>\n",
       "      <td>0.002797</td>\n",
       "      <td>0.002797</td>\n",
       "      <td>0.057084</td>\n",
       "      <td>1.243489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Rara</td>\n",
       "      <td>0610007L01Rik</td>\n",
       "      <td>0.000354</td>\n",
       "      <td>0.000354</td>\n",
       "      <td>0.660728</td>\n",
       "      <td>0.179977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Klf6</td>\n",
       "      <td>0610007L01Rik</td>\n",
       "      <td>-0.002702</td>\n",
       "      <td>0.002702</td>\n",
       "      <td>0.125995</td>\n",
       "      <td>0.899648</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  source         target  coef_mean  coef_abs         p     -logp\n",
       "0  Mef2c  0610007L01Rik  -0.000324  0.000324  0.741978  0.129609\n",
       "1  Gata1  0610007L01Rik   0.002261  0.002261  0.149212  0.826197\n",
       "2   Fli1  0610007L01Rik   0.002797  0.002797  0.057084  1.243489\n",
       "3   Rara  0610007L01Rik   0.000354  0.000354  0.660728  0.179977\n",
       "4   Klf6  0610007L01Rik  -0.002702  0.002702  0.125995  0.899648"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "links.links_dict[\"Ery_0\"].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fitting GRN again...\n",
      "calculating GRN in Ery_0\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e6fd01e1247249b59d2c46311e9b0c9b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/1999 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 491 genes\n",
      "calculating GRN in Ery_1\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "08d1dc39f6e7437bb5350f8aef834d20",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/1999 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 510 genes\n",
      "calculating GRN in Ery_2\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d094e883cd9f4e65976e92c2a358ce8f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/1999 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 548 genes\n",
      "calculating GRN in Ery_3\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bc6534eb47854a898aba5bc62526d360",
       "version_major": 2,
       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 552 genes\n",
      "calculating GRN in Ery_4\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a56996982eff4f14b2cae87539233e23",
       "version_major": 2,
       "version_minor": 0
      },
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       "  0%|          | 0/1999 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 573 genes\n",
      "calculating GRN in Ery_5\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4d3722070f2c4fd58d9635e2b39ddf75",
       "version_major": 2,
       "version_minor": 0
      },
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       "  0%|          | 0/1999 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 579 genes\n",
      "calculating GRN in Ery_6\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1fcd33aaae634f7f8989197acb35d85b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/1999 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 604 genes\n",
      "calculating GRN in Ery_7\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7bd1148ac5854808910f2f1483711047",
       "version_major": 2,
       "version_minor": 0
      },
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       "  0%|          | 0/1999 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 538 genes\n",
      "calculating GRN in Ery_8\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1a2ec028c5a04576a33690be4d07a2a4",
       "version_major": 2,
       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 566 genes\n",
      "calculating GRN in Ery_9\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "42a0bfa68026492f944db874fc52f6bb",
       "version_major": 2,
       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 594 genes\n",
      "calculating GRN in GMP_0\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fd2b8e5ed93445bba2f7ae6076e532c2",
       "version_major": 2,
       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 458 genes\n",
      "calculating GRN in GMP_1\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1ea145b3484f442bb479ccfcff000abb",
       "version_major": 2,
       "version_minor": 0
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 509 genes\n",
      "calculating GRN in GMP_2\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "55c402ee5f8143bebb14b5e7e3ebbce3",
       "version_major": 2,
       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 483 genes\n",
      "calculating GRN in GMPl_0\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c8be09f10901401eb0cf718078aa3fba",
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       "version_minor": 0
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 515 genes\n",
      "calculating GRN in GMPl_1\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e6753170ca6f45628a505f5005d5c18d",
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       "version_minor": 0
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 491 genes\n",
      "calculating GRN in Gran_0\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5edb7710a6e94ff1a60dbc8499a521a8",
       "version_major": 2,
       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 494 genes\n",
      "calculating GRN in Gran_1\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fa5d0ad4b31a43e58b70018cd9dbf33d",
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       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 497 genes\n",
      "calculating GRN in Gran_2\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6fd4c229a597490f887fb6602a7362bc",
       "version_major": 2,
       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 536 genes\n",
      "calculating GRN in Gran_3\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "791a15b88cfc4208a53870a6933c3ece",
       "version_major": 2,
       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 543 genes\n",
      "calculating GRN in MEP_0\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6a1eff406b094563acbbcf161fcd105e",
       "version_major": 2,
       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 522 genes\n",
      "calculating GRN in Mk_0\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c600d1e9ea6e40d38001d9faa44e4036",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/1999 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 480 genes\n",
      "calculating GRN in Mo_0\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "13678a7491fc4f1fa48c1332f1c3d766",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/1999 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 504 genes\n",
      "calculating GRN in Mo_1\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d0d0590bc2544f40a22af2c16f23618a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/1999 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 534 genes\n",
      "calculating GRN in Mo_2\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f7e4084ece3c42daa972d36e612a98e9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/1999 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genes_in_gem: 1999\n",
      "models made for 512 genes\n"
     ]
    }
   ],
   "source": [
    "links.filter_links(p=0.001, weight=\"coef_abs\", threshold_number=2000)\n",
    "oracle.get_cluster_specific_TFdict_from_Links(links_object=links)\n",
    "oracle.fit_GRN_for_simulation(alpha=10, use_cluster_specific_TFdict=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.00000000e+00,  3.19123961e-03,  0.00000000e+00, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "       [ 0.00000000e+00,  6.39196081e-05,  0.00000000e+00, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "       [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "       ...,\n",
       "       [ 0.00000000e+00,  3.55902294e-03,  0.00000000e+00, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "       [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "       [ 0.00000000e+00,  0.00000000e+00, -1.51553339e-04, ...,\n",
       "         0.00000000e+00,  0.00000000e+00,  0.00000000e+00]])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oracle.simulate_shift(perturb_condition={\"Gata1\": 0.0}, n_propagation=3) \n",
    "# Fold change is stored here.\n",
    "oracle.adata.layers['delta_X']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is not necessary but it's a nice visual: perturbation response displayed as a vector field. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x324 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 259,
       "width": 349
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 989.28x324 with 3 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 292,
       "width": 940
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "oracle.estimate_transition_prob(n_neighbors=200,\n",
    "                                knn_random=True, \n",
    "                                sampled_fraction=1)\n",
    "oracle.calculate_embedding_shift(sigma_corr=0.05)\n",
    "oracle.calculate_p_mass(smooth=0.8, n_grid=40, n_neighbors=200)\n",
    "oracle.calculate_mass_filter(min_mass=0.01, plot=False)\n",
    "oracle.plot_cluster_whole(s=10)\n",
    "oracle.plot_simulation_flow_on_grid(scale=0.5, show_background=False)\n",
    "plt.show()\n",
    "sc.pl.draw_graph(oracle.adata, color=[\"Gata1\", oracle.cluster_column_name],\n",
    "                 layer=\"imputed_count\", use_raw=False, cmap=\"viridis\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Troubleshooting with CellOracle\n",
    "\n",
    "Here are many types of errors we have encountered while using CellOracle, with overly terse suggested solutions. \n",
    "\n",
    "\n",
    "> × Encountered error while trying to install package.\n",
    ">\n",
    "> ╰─> fa2\n",
    "\n",
    "Install the package separately, then try the CO install again.\n",
    "\n",
    "> ValueError: gene expression matrix (adata.X) does not seems to be raw_count because it contains negative values.\n",
    "\n",
    "Feed it raw or normalized data, not scaled or centered.\n",
    "\n",
    "> CellOracle takes a long time to run.\n",
    "\n",
    "CellOracle is meant to work with 1,000-3,000 genes, not the full transcriptome. Did you select genes? Also consider downsampling to fewer cells. If you are worried about losing rare cell types, consider [geometric sketching](https://github.com/brianhie/geosketch).\n",
    "\n",
    "> ValueError: Gene {blah} does not have enough regulatory connection in the GRNs. Cannot perform simulation.\n",
    "\n",
    "Get a bigger base GRN or don't prune so aggressively.\n",
    "\n",
    "> ValueError: Gene {blah} is not included in the base GRN; It is not TF or TF motif information is not available. Cannot perform simulation.\n",
    "\n",
    "Get a bigger base GRN. \n",
    "\n",
    "> ValueError: {blah} is not included in the Gene expression matrix.\n",
    "\n",
    "When you select variable genes, make sure you keep the ones you want to perturb. \n",
    "\n",
    "\n",
    "> My desired cell states are not reachable.\n",
    "\n",
    "CellOracle is not intended for extrapolation outside the set of cell states in the training data. The training data need to include the cell state of interest. \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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