demo/tutorial_plot_top20_DE.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## This notebook describes how to visualize model performance on top 20 DE genes\n",
    "\n",
    "NOTE: Run `model_tutorial.ipynb` first since this requires a trained model to be present in `gears_seed1_norman`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'scanpy'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-1-a1deeacc7cef>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'../'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mgears\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mPertData\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mGEARS\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/dfs/user/yhr/testing/GEARS_415/GEARS/demo/../gears/__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0mgears\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mGEARS\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0mpertdata\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mPertData\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/dfs/user/yhr/testing/GEARS_415/GEARS/demo/../gears/gears.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mpickle\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mscanpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0msc\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      8\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'scanpy'"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "sys.path.append('../')\n",
    "\n",
    "from gears import PertData, GEARS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Found local copy...\n",
      "Local copy of pyg dataset is detected. Loading...\n",
      "Done!\n",
      "Local copy of split is detected. Loading...\n",
      "Simulation split test composition:\n",
      "combo_seen0:9\n",
      "combo_seen1:52\n",
      "combo_seen2:18\n",
      "unseen_single:37\n",
      "Done!\n",
      "Creating dataloaders....\n",
      "Done!\n"
     ]
    }
   ],
   "source": [
    "pert_data = PertData('./data')\n",
    "pert_data.load(data_name = 'norman')\n",
    "pert_data.prepare_split(split = 'simulation', seed = 1)\n",
    "pert_data.get_dataloader(batch_size = 32, test_batch_size = 128)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "gears_model = GEARS(pert_data, device = 'cuda:8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "gears_model.load_pretrained('../gears_seed1_norman')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1188x324 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gears_model.plot_perturbation('FOSB+CEBPB')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "deepamp",
   "language": "python",
   "name": "deepamp"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}