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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e10ac0c9-40ce-41fb-b6fa-3d62b76f2e57",
   "metadata": {},
   "outputs": [],
   "source": [
    "from geneformer import InSilicoPerturber\n",
    "from geneformer import InSilicoPerturberStats\n",
    "from geneformer import EmbExtractor"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbd6851c-060e-4967-b816-e605ffe58b23",
   "metadata": {
    "tags": []
   },
   "source": [
    "### in silico perturbation in deletion mode to determine genes whose deletion in the dilated cardiomyopathy (dcm) state significantly shifts the embedding towards non-failing (nf) state"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c53e98cd-c603-4878-82ba-db471181bb55",
   "metadata": {},
   "outputs": [],
   "source": [
    "# first obtain start, goal, and alt embedding positions\n",
    "# this function was changed to be separate from perturb_data\n",
    "# to avoid repeating calcuations when parallelizing perturb_data\n",
    "cell_states_to_model={\"state_key\": \"disease\", \n",
    "                      \"start_state\": \"dcm\", \n",
    "                      \"goal_state\": \"nf\", \n",
    "                      \"alt_states\": [\"hcm\"]}\n",
    "\n",
    "filter_data_dict={\"cell_type\":[\"Cardiomyocyte1\",\"Cardiomyocyte2\",\"Cardiomyocyte3\"]}\n",
    "\n",
    "embex = EmbExtractor(model_type=\"CellClassifier\",\n",
    "                     num_classes=3,\n",
    "                     filter_data=filter_data_dict,\n",
    "                     max_ncells=1000,\n",
    "                     emb_layer=0,\n",
    "                     summary_stat=\"exact_mean\",\n",
    "                     forward_batch_size=256,\n",
    "                     nproc=16)\n",
    "\n",
    "state_embs_dict = embex.get_state_embs(cell_states_to_model,\n",
    "                                       \"path/to/model\",\n",
    "                                       \"path/to/input_data\",\n",
    "                                       \"path/to/output_directory\",\n",
    "                                       \"output_prefix\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "981e1190-62da-4543-b7d3-6e2a2d6a6d56",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "isp = InSilicoPerturber(perturb_type=\"delete\",\n",
    "                        perturb_rank_shift=None,\n",
    "                        genes_to_perturb=\"all\",\n",
    "                        combos=0,\n",
    "                        anchor_gene=None,\n",
    "                        model_type=\"CellClassifier\",\n",
    "                        num_classes=3,\n",
    "                        emb_mode=\"cell\",\n",
    "                        cell_emb_style=\"mean_pool\",\n",
    "                        filter_data=filter_data_dict,\n",
    "                        cell_states_to_model=cell_states_to_model,\n",
    "                        state_embs_dict=state_embs_dict,\n",
    "                        max_ncells=2000,\n",
    "                        emb_layer=0,\n",
    "                        forward_batch_size=400,\n",
    "                        nproc=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0525a663-871a-4ce0-a135-cc203817ffa9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# outputs intermediate files from in silico perturbation\n",
    "isp.perturb_data(\"path/to/model\",\n",
    "                 \"path/to/input_data\",\n",
    "                 \"path/to/output_directory\",\n",
    "                 \"output_prefix\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f8aadabb-516a-4dc0-b307-6de880e64e26",
   "metadata": {},
   "outputs": [],
   "source": [
    "ispstats = InSilicoPerturberStats(mode=\"goal_state_shift\",\n",
    "                                  genes_perturbed=\"all\",\n",
    "                                  combos=0,\n",
    "                                  anchor_gene=None,\n",
    "                                  cell_states_to_model=cell_states_to_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ffecfae6-e737-43e3-99e9-fa37ff46610b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# extracts data from intermediate files and processes stats to output in final .csv\n",
    "ispstats.get_stats(\"path/to/input_data\",\n",
    "                   None,\n",
    "                   \"path/to/output_directory\",\n",
    "                   \"output_prefix\")"
   ]
  }
 ],
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