{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "340b550f-303d-4170-9324-99f74ee2a980",
   "metadata": {},
   "source": [
    "# Tutorial 2: Generating Attributions\n",
    "\n",
    "This first part of this tutorial shows how to generate new attribution scores using integrated gradients and SCimilarity. \n",
    "\n",
    "The second section details how to integrate new attributions with pre-computed attributions\n",
    "\n",
    "Before running this tutorial, you need to:\n",
    "\n",
    "1. Download the SCimilarity model from https://zenodo.org/records/15729925.\n",
    "2. Download the cell type-level attributions you are interested in from https://zenodo.org/communities/signature/. For this tutorial, you can download the relevant attributions from https://zenodo.org/records/15794176. The file can be extracted by running `tar -xzf celltype_attributions.tar.gz`. This will produce the \"celltype_attributions\" folder needed for the tutorial below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d01c3367-2a22-4cc5-b950-ee6fd95de744",
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "import numpy as np\n",
    "import os\n",
    "from os.path import join\n",
    "import pandas as pd\n",
    "import scanpy as sc\n",
    "from scipy import sparse\n",
    "\n",
    "from SIGnature import SIGnature, SCimilarity, Meta\n",
    "from SIGnature.utils import align_dataset, lognorm_counts\n",
    "from tqdm import tqdm\n",
    "import warnings\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d75bd0ec-0c5c-49a2-9071-a48d41f0deac",
   "metadata": {},
   "source": [
    "# Part 1: Generate Attributions for New Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df81f956-d8a9-4ca3-9786-c44f8f89c896",
   "metadata": {},
   "source": [
    "### Load SCimilarity Model and Attributions TileDB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "eeb0a255-bc64-4dc9-a7b3-1d01f94a4a00",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Path to Scimilarity Model Downloaded from Zenodo (https://zenodo.org/records/15729925)\n",
    "scim_model_path = \"/home/scimilarity_model\"\n",
    "## You want to use a GPU with the SCimilarity model if you are generating attributions\n",
    "## If you do not have access to gpu set use_gpu = False\n",
    "scim = SCimilarity(model_path=scim_model_path, use_gpu=True)\n",
    "\n",
    "sig = SIGnature(gene_order=scim.gene_order, model=scim.model, use_gpu=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b626c3a-eb71-42e4-864a-9127467abf30",
   "metadata": {},
   "source": [
    "### Load dataset\n",
    "\n",
    "Load your custom dataset. This tutorial shows randomly generated cells. 5000 are entirely random and 500 selectively upregulate MS1.\n",
    "\n",
    "To generate attributions, AnnData needs to be compatible with SCimilarity:\n",
    "\n",
    "1. Raw counts in .X and .layers['counts']\n",
    "2. Genes named using HGNC symbols\n",
    "\n",
    "To use downstream \"Meta\" object for analysis, `obs` in the AnnData needs to include:\n",
    "\n",
    "1. Disease label\n",
    "2. Sample label\n",
    "3. Study label\n",
    "4. Tissue label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2465a152-c012-4f4b-9e8b-74f2958abd01",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Load custom data\n",
    "# adata = sc.read_h5ad('your_path')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2313afdc-7ee8-48b4-afaa-68e11f4858e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_random_cell(\n",
    "    n_genes, high_gene_indices=None, high_level_range=(5, 10), rs=114\n",
    "):\n",
    "    \"\"\"\n",
    "    Generate a random cell with counts, ensuring modest randomized high levels for specific genes.\n",
    "\n",
    "    Parameters:\n",
    "    - n_genes: int, total number of genes.\n",
    "    - high_gene_indices: list of ints, indices of genes to set to high levels (default: None).\n",
    "    - high_level_range: tuple, range of high levels (default: (5, 10)).\n",
    "    - rs: int, random seed for reproducibility.\n",
    "\n",
    "    Returns:\n",
    "    - counts_zinb: array of gene counts.\n",
    "    \"\"\"\n",
    "    np.random.seed(rs)\n",
    "\n",
    "    ## Generate random counts using Zero-Inflated Negative Binomial (ZINB)\n",
    "    counts_zinb = np.random.negative_binomial(n=1, p=0.1, size=n_genes)\n",
    "    ## 80% zeros (typical for scRNA-seq)\n",
    "    zero_mask = np.random.random(n_genes) < 0.8\n",
    "    counts_zinb[zero_mask] = 0\n",
    "\n",
    "    ## Set randomized high count levels for specific gene indices\n",
    "    if high_gene_indices is not None:\n",
    "        high_levels = np.random.randint(\n",
    "            low=high_level_range[0],\n",
    "            high=high_level_range[1] + 1,\n",
    "            size=len(high_gene_indices),\n",
    "        )\n",
    "        counts_zinb[high_gene_indices] = high_levels\n",
    "\n",
    "    return counts_zinb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8271675d-f62c-4862-90e9-494d343afcbd",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Generate 5000 random cells\n",
    "ng = 28231  # Number of genes\n",
    "nc = 5000  # Number of cells\n",
    "\n",
    "count_list = [generate_random_cell(ng, rs=i) for i in range(nc)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "69421088-2e42-4f10-a211-1a341a0eee89",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The following genes are not included: CTB-35F21.5,RP11-800A3.7,CTC-246B18.10,RP11-123K3.9,RP1-55C23.7,FAM65B,AC097495.2,C19orf35,CTD-2105E13.14,HYI-AS1,RP11-295G20.2,CTC-490G23.2,RP11-196G18.3\n"
     ]
    }
   ],
   "source": [
    "## Generate 500 random cells with high MS1 gene counts\n",
    "ms1_genes = ['S100A8', 'S100A12', 'RETN', 'CLU', 'MCEMP1', 'IL1R2', 'CYP1B1', 'SELL', \n",
    "             'ALOX5AP', 'SLC39A8', 'PLAC8', 'ACSL1', 'CD163', 'VCAN', 'HP', 'CTSD', \n",
    "             'LGALS1', 'THBS1', 'CES1', 'S100P', 'ANXA6', 'VNN2', 'NAMPT', 'HAMP', \n",
    "             'DYSF', 'SDF2L1', 'NFE2', 'SLC2A3', 'BASP1', 'ADGRG3', 'SOD2', 'CTSA', \n",
    "             'PADI4', 'CALR', 'SOCS3', 'NKG7', 'FLOT1', 'IL1RN', 'ZDHHC19', 'LILRA5', \n",
    "             'ASGR2', 'FAM65B', 'MNDA', 'STEAP4', 'NCF4', 'LBR', 'RP11-295G20.2', \n",
    "             'UBR4', 'PADI2', 'NCF1', 'LINC00482', 'RUNX1', 'RRP12', 'HSPA1A', \n",
    "             'FLOT2', 'ANPEP', 'CXCR1', 'ECE1', 'ADAM19', 'RP11-196G18.3', 'IL4R', \n",
    "             'DNAJB11', 'FES', 'MBOAT7', 'SNHG25', 'RP1-55C23.7', 'CPEB4', \n",
    "             'PRR34-AS1', 'HSPA1B', 'LINC01001', 'C1QC', 'SBNO2', 'GTSE1', 'FOLR3', \n",
    "             'STAB1', 'PLK1', 'HYI-AS1', 'LINC01281', 'TNNT1', 'AC097495.2', \n",
    "             'CTB-35F21.5', 'C19orf35', 'AC109826.1', 'RP11-800A3.7', 'LILRA6', \n",
    "             'PDLIM7', 'NPLOC4', 'C15orf48', 'APOBR', 'CSF2RB', 'CTD-2105E13.14', \n",
    "             'C1QB', 'RP11-123K3.9', 'IQGAP3', 'GAPLINC', 'CTC-490G23.2', 'JAK3', \n",
    "             'CTC-246B18.10', 'MYO5B']\n",
    "\n",
    "gene_list = sig.check_genes(ms1_genes)\n",
    "ms1_idx = [scim.gene_order.index(x) for x in gene_list]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "597ff2f1-c1d9-456c-89c6-2ed6250dbf44",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Generate 500 cells with high gene counts in MS1 genes\n",
    "ncl = 500\n",
    "count_list_ms1 = [\n",
    "    generate_random_cell(ng, high_gene_indices=ms1_idx, high_level_range=(10, 40), rs=i)\n",
    "    for i in range(ncl)\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3a66cec1-88fb-4263-86fd-09b6f04dd955",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Combine count matrices\n",
    "full_count_list = count_list + count_list_ms1\n",
    "count_mat = np.vstack(full_count_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "107ac020-b94c-4f98-b89f-eb519f678bf4",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Convert to AnnData\n",
    "adata = sc.AnnData(count_mat)\n",
    "adata.layers[\"counts\"] = count_mat\n",
    "adata.var = pd.DataFrame(index=scim.gene_order)\n",
    "adata.obs = pd.DataFrame(index=range(adata.shape[0]))\n",
    "## Add disease labels for random cells and MS1 cells\n",
    "adata.obs[\"disease\"] = [\"Condition 1\" for _ in range(nc)] + [\n",
    "    \"Condition 2\" for _ in range(ncl)\n",
    "]\n",
    "## Add sample labels for each condition\n",
    "adata.obs[\"sample\"] = [\"Sample \" + str(int(x / 100)) \\\n",
    "                       for x in range(adata.obs.shape[0])]\n",
    "adata.layers[\"counts\"] = sparse.csr_matrix(count_mat)\n",
    "## Need to include sample, study, disease, and tissue to use standard \"Meta\" functions\n",
    "adata.obs[\"study\"] = \"Test Study\"\n",
    "adata.obs[\"tissue\"] = \"Test Tissue\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89287600-b5ce-4163-ba76-dd97dc26c2c0",
   "metadata": {},
   "source": [
    "### Align Dataset to SCimilarity Genes\n",
    "\n",
    "Attributions collected against SCimilarity model need to be aligned to SCimilarity gene order and then log-normalized."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d1aefef9-1823-435c-a71c-f692536733c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "adata = align_dataset(adata, target_gene_order=scim.gene_order)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "59c5dc64-b0c8-41ad-aafa-232d19775901",
   "metadata": {},
   "outputs": [],
   "source": [
    "adata = lognorm_counts(adata)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37f5d7a8-9aa0-4929-a53f-997c417d3818",
   "metadata": {},
   "source": [
    "### Generate attributions\n",
    "\n",
    "Buffer size controls how many cells processed at once. Can adjust to fit on GPU."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "edd7a7dc-5900-4b26-b252-2d783482e05c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:06<00:00,  1.02s/it]\n"
     ]
    }
   ],
   "source": [
    "start = datetime.now()\n",
    "att = sig.calculate_attributions(X=adata.X, buffer_size=1000)\n",
    "\n",
    "## if you want to directly save npz_file, run below\n",
    "# npz_file='custom_data.npz'\n",
    "# att = sig.calculate_attributions(X=adata.X, buffer_size=1000, npz_path=npz_file)\n",
    "stop = datetime.now()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ae54f9bc-7ba5-4682-9f9a-749bf8558ff0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0:00:09.300615\n"
     ]
    }
   ],
   "source": [
    "print(stop - start)  # ~10 seconds for the 5500 cells on GPU"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ac05f59c-cf95-420c-a513-191817004743",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.1875074, 0.       , 0.       , ..., 0.       , 0.       ,\n",
       "        0.       ]], dtype=float32)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "att[0].toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "83b358d9-6b9c-4f5c-b0fc-62208aab0d11",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.2711536, 0.       , 0.       , ..., 0.       , 0.       ,\n",
       "        0.       ]], dtype=float32)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata.X[0].toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "18126330-b1c6-486d-9fd8-de000c9a061a",
   "metadata": {},
   "outputs": [],
   "source": [
    "## save attributions if not saved above\n",
    "npz_file = \"custom_data.npz\"\n",
    "sparse.save_npz(matrix=att, file=npz_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f79704ee-95b7-4491-a498-f43ff6b7ba2e",
   "metadata": {},
   "source": [
    "# Part 2: Integrate new data with pre-computed attributions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d29af9b-0b69-4dab-9be6-4e459568837f",
   "metadata": {},
   "source": [
    "### Create a tiledb for integrating with known matrices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "de2086b5-b971-40ba-9f5f-e3ec09907bd7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimizing custom_data\n",
      "Fragments before consolidation: 1\n",
      "Fragments after consolidation: 1\n"
     ]
    }
   ],
   "source": [
    "## Overwrite will take tiledb with the same name [custom_tiledb] \n",
    "## and overwrite it with your new one\n",
    "sig.create_tiledb(npz_path=npz_file, overwrite=True, \n",
    "                  attribution_tiledb_uri='custom_data')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb6e801e-511f-4ce1-8511-542078002777",
   "metadata": {},
   "source": [
    "### Search existing tiledbs and new tiledb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "51685e01-a069-4a0f-800f-b2d43459a7ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Path to cell type attributions downloaded from Zenodo (https://zenodo.org/records/15794176)\n",
    "ct_base = \"/home/celltype_attributions\"\n",
    "all_ct = os.listdir(ct_base)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "f2fddbb6-4dee-4e05-98c7-b2b87ddfa6e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Analyze all monocyte/macrophage cell populations in database\n",
    "ctoi = [\n",
    "    \"alveolar macrophage\",\n",
    "    \"classical monocyte\",\n",
    "    \"intermediate monocyte\",\n",
    "    \"macrophage\",\n",
    "    \"non-classical monocyte\",\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2d8625d-665f-4259-9100-bed6fdb429d7",
   "metadata": {},
   "source": [
    "#### Check genes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f86990c0-febf-49de-9d82-d3b6e11b87e0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The following genes are not included: CTB-35F21.5,RP11-800A3.7,CTC-246B18.10,RP11-123K3.9,RP1-55C23.7,FAM65B,AC097495.2,C19orf35,CTD-2105E13.14,HYI-AS1,RP11-295G20.2,CTC-490G23.2,RP11-196G18.3\n"
     ]
    }
   ],
   "source": [
    "gene_list = sig.check_genes(ms1_genes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9bc1d52-f19c-45b1-9487-8a2e91714569",
   "metadata": {},
   "source": [
    "#### Calculate SIGnature Scores for each Cell Type\n",
    "\n",
    "Iterate through tiledb of each cell type, calculate score, concatenate the metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "df079d83-ad4a-4562-b333-84ce41b7c826",
   "metadata": {},
   "outputs": [],
   "source": [
    "score_name = \"MS1\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "18b720d2-7bd6-40c1-8fb9-3d3673b5dea8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5/5 [00:26<00:00,  5.30s/it]\n"
     ]
    }
   ],
   "source": [
    "meta_list = []\n",
    "for ct in tqdm(ctoi):\n",
    "    ## Get specific tiledb path for location of interest\n",
    "    ct_path = join(ct_base, ct)\n",
    "    ## Load attributions tiledb path for given cell type\n",
    "    att_tdb_path = join(ct_path, \"attributions\")\n",
    "    ## Calculate\n",
    "    results = sig.query_attributions(\n",
    "        gene_list,\n",
    "        return_aggregate=True,\n",
    "        aggregate_type=\"mean\",\n",
    "        attribution_tiledb_uri=att_tdb_path,\n",
    "    )\n",
    "\n",
    "    ## Example including weights\n",
    "    # weight_list = np.random.choice([0.5, 1, 2], len(gene_list)).tolist()\n",
    "    # results = sig.query_attributions(gene_list, return_aggregate=True, \n",
    "    #               aggregate_type='mean', weights = weight_list, \n",
    "    #               attribution_tiledb_uri=att_tdb_path)\n",
    "\n",
    "    ## Example getting individual genes\n",
    "    # results = sig.query_attributions(gene_list, return_aggregate=False, \n",
    "    #               attribution_tiledb_uri=att_tdb_path)\n",
    "\n",
    "    ## Load corresponding cell metadata\n",
    "    ct_path = join(ct_base, ct)\n",
    "    meta = pd.read_csv(join(ct_path, \"cell_metadata.csv.gz\"), index_col=0)\n",
    "\n",
    "    ## Put score\n",
    "    meta[score_name] = results\n",
    "    meta_list.append(meta.copy())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2fdb2886-9420-40ce-953f-e202776adf98",
   "metadata": {},
   "source": [
    "#### load in new data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "e3a6455a-797d-4a9f-a4c3-c9e72c748050",
   "metadata": {},
   "outputs": [],
   "source": [
    "big_meta = pd.concat(meta_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "bc9acdfb-4905-4fb8-869e-0607aa6df6b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "momac_meta = Meta(big_meta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "926d7af7-a831-49d7-857f-f6562da48701",
   "metadata": {},
   "outputs": [],
   "source": [
    "momac_meta.subset_invivo()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "121a3bc9-a946-4651-afb6-83b6e57a838c",
   "metadata": {},
   "outputs": [],
   "source": [
    "momac_meta.subset_hq()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b63cbd2b-eb76-4c05-89f4-8a97420212b3",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Calculate\n",
    "results = sig.query_attributions(\n",
    "    gene_list,\n",
    "    return_aggregate=True,\n",
    "    aggregate_type=\"mean\",\n",
    "    attribution_tiledb_uri=\"custom_data\",\n",
    ")\n",
    "\n",
    "## Load corresponding cell metadata\n",
    "nmeta = adata.obs\n",
    "nmeta\n",
    "\n",
    "## Put score\n",
    "nmeta[score_name] = results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a60b9628-8115-487c-93a8-f092a7e68621",
   "metadata": {},
   "source": [
    "#### Integrate datasets and clean disease names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "1c4737ab-58e7-4b0b-ba85-4860f4eb64fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "momac_meta.append(nmeta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "386d6c34-86ff-447f-bc53-94f16336efa9",
   "metadata": {},
   "outputs": [],
   "source": [
    "figure_disname_dict = {\n",
    "    \"atopic eczema\": \"Atopic Dermatitis\",\n",
    "    \"COVID-19;healthy\": \"COVID-19 & Healthy (Mixed)\",\n",
    "    \"Epstein-Barr virus infection;hemophagocytic syndrome\": \"EBV-Associated HLH\",\n",
    "    \"Immune dysregulation-polyendocrinopathy-enteropathy-X-linked syndrome\": \"IPEX\",\n",
    "    \"mucocutaneous lymph node syndrome\": \"Kawasaki Disease\",\n",
    "    \"systemic scleroderma;interstitial lung disease\": \"SSC-ILD\",\n",
    "    \"thrombocytopenia\": \"Severe Fever Thrombocytopenia Syndrome\",\n",
    "}\n",
    "\n",
    "momac_meta.df[\"disease\"] = [\n",
    "    figure_disname_dict.get(x, x) for x in momac_meta.df[\"disease\"]\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6ba2596-5ef8-4ab5-965a-e398934f6caa",
   "metadata": {},
   "source": [
    "#### Calculate hit percentage per sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "b8bb2ad8-0b3e-4df4-909d-34fa75a26409",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define hits\n",
    "hit_col = \"MS1\"\n",
    "## 90th percentile\n",
    "momac_meta.add_hits(\n",
    "    column_name=hit_col,\n",
    "    mode=\"percentile\",\n",
    "    cut_val=90,\n",
    "    hit_type=\"above\",\n",
    "    string_append=\"__hit90p\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "81956929-1955-4031-8b5b-db020e9df153",
   "metadata": {},
   "outputs": [],
   "source": [
    "# calculate hits per sample\n",
    "samphit_df_90 = momac_meta.samphit_df(\n",
    "    cell_min=25, samp_min=3, hit_col=\"MS1__hit90p\", num_dis=100\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83c4196a-6435-4932-b576-120676510104",
   "metadata": {},
   "source": [
    "#### Plot top diseases by mean hit percentage\n",
    "\n",
    "Condition 2 (initialized with MS1-like cells) shows high levels, but Condition 1 (which was initialized random counts) is very low."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "1c62e949-a280-463a-b8c6-ffeac30b5fae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 400x1300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(4, 13))\n",
    "sns.boxplot(data=samphit_df_90, y=\"disease\", x=\"MS1__hit90p\", showfliers=False)\n",
    "ax.set_yticklabels(ax.get_yticklabels(), ha=\"right\", fontsize=8)\n",
    "\n",
    "for label in ax.get_yticklabels():\n",
    "    if label.get_text() in [\"Condition 1\", \"Condition 2\"]:\n",
    "        label.set_color(\"red\")\n",
    "ax.set_title(\"MS1 Hit Percentage Across Diseases\")\n",
    "ax.set_xlabel(\"Sample-Level MS1 Hit Percentage (%)\")\n",
    "ax.set_ylabel('')\n",
    "\n",
    "x_ticks = ax.get_xticks() * 100\n",
    "ax.set_xticklabels([f\"{int(y)}\" for y in x_ticks]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "561ec3a6-a13f-4ba1-9b90-3894faa84d2c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.18"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}