tumor_example.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "54d366a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import scanpy as sc\n",
    "import pandas as pd\n",
    "from scipy.sparse import csr_matrix\n",
    "from scipy import sparse\n",
    "import scipy.io\n",
    "import os\n",
    "import anndata as ad # Anndata version must > 0.8\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set_theme(style='white')\n",
    "from utils_unknown import *\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dec41914",
   "metadata": {},
   "source": [
    "## Identifying tumor cell types (unknown cell types):  using the Healthy Adult Human Large Atlas (HHLA) to annotate BCC tumor sample data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "de18bc2b",
   "metadata": {},
   "outputs": [],
   "source": [
    "output_name = \"BCC_samples\"\n",
    "out_dir = os.path.join(\"case_study\", output_name)\n",
    "\n",
    "reference_data_path = \"data/Reference/HHLA_atlas.h5ad\"\n",
    "reference_data = load_reference_data(reference_data_path)\n",
    "SU007_Total_Post = import_query_data(path = 'data/BCC_samples/SU007_Total_Post_vHealthyAdult',\n",
    "                                    mtx_file = 'matrix.mtx.gz',\n",
    "                                    cells_file = 'barcodes.tsv.gz',\n",
    "                                    features_file = 'features.tsv.gz',\n",
    "                                    variable_prefix = \"SU007_Total_Post\",\n",
    "                                    celltype_col = \"celltypes\",\n",
    "                                    add_metrics=False)\n",
    "SU010_Total_Pre = import_query_data(path = 'data/BCC_samples/SU010_Total_Pre_vHealthyAdult',\n",
    "                                    mtx_file = 'matrix.mtx.gz',\n",
    "                                    cells_file = 'barcodes.tsv',\n",
    "                                    features_file = 'features.tsv.gz',\n",
    "                                    variable_prefix = \"SU010_Total_Pre\",\n",
    "                                    celltype_col = \"celltypes\",\n",
    "                                    add_metrics=False)\n",
    "\n",
    "assert reference_data.var.shape[0] == SU010_Total_Pre.var.shape[0]\n",
    "assert reference_data.var.shape[0] == SU007_Total_Post.var.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8f38a3e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "reference_data.obs[\"CellType\"] = reference_data.obs[\"celltypes\"].values\n",
    "\n",
    "concat_adata = sc.AnnData.concatenate(reference_data, SU010_Total_Pre)\n",
    "concat_adata = sc.AnnData.concatenate(concat_adata, SU007_Total_Post)\n",
    "\n",
    "Batch = [\"reference\"]*reference_data.shape[0] \\\n",
    "        + [\"SU010_Total_Pre\"]*SU010_Total_Pre.shape[0] \\\n",
    "        + [\"SU007_Total_Post\"] * SU007_Total_Post.shape[0] \\\n",
    "        \n",
    "concat_adata.obs[\"Batch\"] = Batch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "32b4261c",
   "metadata": {},
   "outputs": [],
   "source": [
    "peaks = concat_adata.var_names.values\n",
    "\n",
    "chrom = [i.split(\":\")[0] for i in peaks]\n",
    "start = [i.split(\":\")[1].split(\"-\")[0] for i in peaks]\n",
    "end = [i.split(\":\")[1].split(\"-\")[1] for i in peaks]\n",
    "\n",
    "concat_adata = make_anndata(\n",
    "    adata = concat_adata, \n",
    "    chrom = chrom, \n",
    "    start = start, \n",
    "    end = end, \n",
    "    path = \"preprocessed_data/BCC_1.h5ad\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "622bc176",
   "metadata": {},
   "source": [
    "Run CACNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ef0c21fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "!python SANGO/CACNN/main.py -i preprocessed_data/BCC_1.h5ad \\\n",
    "                -g hg38 \\\n",
    "                -o output/BCC_1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ff7ab2c",
   "metadata": {},
   "source": [
    "Run GraphTransformer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b2145b02",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "computing PCA\n",
      "    with n_comps=50\n",
      "    finished (0:00:00)\n",
      "computing batch balanced neighbors\n",
      "\tfinished: added to `.uns['neighbors']`\n",
      "\t`.obsp['distances']`, distances for each pair of neighbors\n",
      "\t`.obsp['connectivities']`, weighted adjacency matrix (0:00:07)\n",
      "running Leiden clustering\n",
      "    finished: found 28 clusters and added\n",
      "    'leiden', the cluster labels (adata.obs, categorical) (0:00:05)\n",
      "computing ridge regression\n",
      "\tfinished: `.X` now features regression residuals\n",
      "\t`.layers['X_explained']` stores the expression explained by the technical effect (0:00:00)\n",
      "computing PCA\n",
      "    with n_comps=50\n",
      "    finished (0:00:00)\n",
      "computing batch balanced neighbors\n",
      "\tfinished: added to `.uns['neighbors']`\n",
      "\t`.obsp['distances']`, distances for each pair of neighbors\n",
      "\t`.obsp['connectivities']`, weighted adjacency matrix (0:00:05)\n",
      "100%|█████████████████████████████████████████| 300/300 [12:25<00:00,  2.48s/it]\n",
      "100%|███████████████████████████████████████| 1737/1737 [09:14<00:00,  3.13it/s]\n"
     ]
    }
   ],
   "source": [
    "!python SANGO/GraphTransformer/main.py --data_dir output/BCC_1/CACNN_output.h5ad \\\n",
    "                --train_name_list reference --test_name SU010_Total_Pre SU007_Total_Post \\\n",
    "                --save_path output \\\n",
    "                --save_name BCC_1 \\\n",
    "                --save_unknown --save_rare --no_smote --get_weight "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a76dcbd3",
   "metadata": {},
   "source": [
    "**Note**:After the completion of GraphTransformer training, the representations of all cells are saved to the embedding.h5ad file, and the relationships between cells are saved to the weight.npy file. These files are stored in the folder named BCC_1."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ff4abcc",
   "metadata": {},
   "source": [
    "We first create a dictionary of reference and query datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9abb9df3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total number of query cells: 1737\n"
     ]
    }
   ],
   "source": [
    "data_list = [SU007_Total_Post, SU010_Total_Pre]\n",
    "print(\"total number of query cells: {}\".format(np.sum([i.obs.shape[0] for i in data_list])))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7890233a",
   "metadata": {},
   "source": [
    "select features of datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8f3673ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Atlas': AnnData object with n_obs × n_vars = 100158 × 890130\n",
       "     obs: 'celltypes', 'tissue', 'dataset', 'CellType'\n",
       "     var: 'selected'\n",
       "     uns: 'cell type_colors', 'major cell type_colors', 'spectral_eigenvalue', 'tissue_colors'\n",
       "     obsm: 'X_umap',\n",
       " 'SU007_Total_Post': AnnData object with n_obs × n_vars = 666 × 890130\n",
       "     obs: 'celltypes', 'tissue', 'dataset'\n",
       "     var: 'selected',\n",
       " 'SU010_Total_Pre': AnnData object with n_obs × n_vars = 1071 × 890130\n",
       "     obs: 'celltypes', 'tissue', 'dataset'\n",
       "     var: 'selected'}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "select_features(reference_data)\n",
    "for anndata in data_list:\n",
    "    select_features(anndata)\n",
    "\n",
    "datasets={}\n",
    "datasets[\"Atlas\"] = reference_data\n",
    "for anndata in data_list:\n",
    "    key = (anndata.obs[\"dataset\"])[0]\n",
    "    datasets[key] = anndata\n",
    "datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d7c7ada5",
   "metadata": {},
   "outputs": [],
   "source": [
    "adata = sc.read_h5ad(\"output/BCC_1/embedding.h5ad\")\n",
    "\n",
    "datasets[\"Atlas\"].obs[\"pred_GraphTransformer\"] = adata[adata.obs[\"Batch\"] == \"reference\"].obs[\"Pred\"].values\n",
    "datasets[\"SU010_Total_Pre\"].obs[\"pred_GraphTransformer\"] = adata[adata.obs[\"Batch\"] == \"SU010_Total_Pre\"].obs[\"Pred\"].values\n",
    "datasets[\"SU007_Total_Post\"].obs[\"pred_GraphTransformer\"] = adata[adata.obs[\"Batch\"] == \"SU007_Total_Post\"].obs[\"Pred\"].values\n",
    "\n",
    "datasets[\"Atlas\"].obsm[\"X\"] = adata[adata.obs[\"Batch\"] == \"reference\"].X\n",
    "datasets[\"SU010_Total_Pre\"].obsm[\"X\"] = adata[adata.obs[\"Batch\"] == \"SU010_Total_Pre\"].X\n",
    "datasets[\"SU007_Total_Post\"].obsm[\"X\"] = adata[adata.obs[\"Batch\"] == \"SU007_Total_Post\"].X\n",
    "\n",
    "integrated_adata = sc.AnnData.concatenate(datasets[\"Atlas\"], datasets[\"SU010_Total_Pre\"])\n",
    "integrated_adata = sc.AnnData.concatenate(integrated_adata, datasets[\"SU007_Total_Post\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "519dcc2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Plot UMAP using spectral embeddings\n",
    "integrated_adata = get_umap(integrated_adata, out_dir, use_rep = \"X\", save = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7778f2c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "reference = integrated_adata[integrated_adata.obs['dataset'] == \"reference\",:].copy()\n",
    "reference.obs[\"celltypes\"] =  curate_celltype_names(reference.obs[\"celltypes\"], atlas = \"HealthyAdult\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "444928b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = integrated_adata[integrated_adata.obs['dataset'] != \"reference\",:].copy()\n",
    "query.obs_names = [j+\"#\"+i+\"_\"+j for i,j in zip(SU010_Total_Pre.obs_names.values, SU010_Total_Pre.obs[\"dataset\"].values)] \\\n",
    "                    + [j+\"#\"+i+\"_\"+j for i,j in zip(SU007_Total_Post.obs_names.values, SU007_Total_Post.obs[\"dataset\"].values)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "955f6db2",
   "metadata": {},
   "outputs": [],
   "source": [
    "projection_allcells = pd.read_table(\"data/BCC_samples/BCC_study_metadata.csv\", index_col = 0, sep = \",\")\n",
    "projection_allcells.index = [projection_allcells.loc[i,\"Group\"] + \"#\" + i for i in projection_allcells.index]\n",
    "sample_names = [\"SU010_Total_Pre\", \"SU007_Total_Post\"]\n",
    "projection = projection_allcells[projection_allcells[\"Group\"].isin(sample_names)]\n",
    "query.obs = pd.merge(query.obs, projection, left_index=True, right_index=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53a5937a",
   "metadata": {},
   "source": [
    "We utilized the attention weights between cells, saved in the 'weight.npy' file obtained from GraphTransformer, to compute the uncertainty score for each cell in the query data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "eb9ca41e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 1737 × 890130\n",
       "    obs: 'celltypes', 'tissue', 'dataset', 'CellType', 'pred_GraphTransformer', 'batch', 'UMAP_1', 'UMAP_2', 'Clusters', 'Group', 'depth', 'FRIP', 'Barcodes', 'Internal_Name', 'Group_Barcode', 'true_label', 'uncertainty_score_step1', 'pred_y'\n",
       "    var: 'selected-0-0', 'selected-1-0', 'selected-1'\n",
       "    obsm: 'X', 'X_umap', 'kernel_distance', 'distance', 'indices', 'neighbors_labels'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weight_path = \"output/BCC_1/weight.npy\"\n",
    "get_uncertainty_score_step1(query, reference, weight_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76d04b3b",
   "metadata": {},
   "source": [
    "We then project query cells into the same UMAP coordinates as original publication for better comparisons, and perform cluster-level assignment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e30e42bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "query.obsm[\"X_umap\"] = np.array(query.obs[[\"UMAP_1\", \"UMAP_2\"]])\n",
    "\n",
    "uncertainty_threshold = 0.2\n",
    "pred_y_unknown = np.array(query.obs[\"pred_y\"].values)\n",
    "uncertainty_score = np.array(query.obs[\"uncertainty_score_step1\"].values)\n",
    "pred_y_unknown[uncertainty_score > uncertainty_threshold] = \"unknown\"\n",
    "query.obs[\"pred_y_unknown\"] = pred_y_unknown\n",
    "\n",
    "query_annotated = cluster_assign(query, use_rep = \"X\", cluster_col = \"Clusters\", UMAP=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5db95cfd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 7680x5760 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2183.4x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(dpi=1200)\n",
    "sc.pl.umap(query_annotated, \n",
    "           color = ['true_label', \"cluster_annotation\", 'uncertainty_score_step1'], \n",
    "           title=[\"\", \"\", \"\"], \n",
    "           legend_loc = \"on data\", \n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "aaa2e6f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 7680x5760 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pred_col = 'cluster_annotation'\n",
    "true_col = 'true_label'\n",
    "\n",
    "plt.rcParams['font.weight'] = \"heavy\"\n",
    "plt.figure(dpi=1200)\n",
    "\n",
    "sankey(\n",
    "    query_annotated.obs[pred_col], query_annotated.obs[true_col], aspect=10,\n",
    "    fontsize=10, leftLabels=[\"unknown\", \"Mural\", \"Endothelial\", \"Immune Cells\"],\n",
    "    rightLabels=['Tumor', 'Fibroblasts', 'Endothelial',\n",
    "                 'B', 'CD8 TEx', 'Effector CD8 T',\n",
    "                 'Memory CD8 T', 'Myeloid', 'NK1', 'NK2', 'Naive CD4 T',\n",
    "                 'Naive CD8 T', 'Plasma B', 'Tfh', 'Th1', 'Th17', 'Treg']\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "4141ed2f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                   0\n",
      "0  SU010_Total_Pre#SU010_Total_Pre#TACTGCCAGTTGAA...\n",
      "1  SU010_Total_Pre#SU010_Total_Pre#AGCGATTAGAACTA...\n",
      "2  SU010_Total_Pre#SU010_Total_Pre#GCCCGAAAGGCACC...\n",
      "3  SU010_Total_Pre#SU010_Total_Pre#TCTCAGCCAGTTGG...\n",
      "4  SU010_Total_Pre#SU010_Total_Pre#TATGTGGGTGAGGG...\n"
     ]
    }
   ],
   "source": [
    "immune_cells = pd.DataFrame(query_annotated[query_annotated.obs[\"cluster_annotation\"] == \"Immune Cells\"].obs.index)\n",
    "print(immune_cells.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff15b46e",
   "metadata": {},
   "source": [
    "## Identifying subtypes:  using BCC_TIL_atlas to annotate BCC immune subtype cells"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ec85969f",
   "metadata": {},
   "outputs": [],
   "source": [
    "reference_data_path = \"data/Reference/BCC_TIL_atlas.h5ad\"\n",
    "reference_data = load_reference_data(reference_data_path)\n",
    "SU007_Total_Post = import_query_data(path = 'data/BCC_samples/SU007_Total_Post_vBCC',\n",
    "                                    mtx_file = 'matrix.mtx.gz',\n",
    "                                    cells_file = 'barcodes.tsv.gz',\n",
    "                                    features_file = 'features.tsv.gz',\n",
    "                                    variable_prefix = \"SU007_Total_Post\",\n",
    "                                    celltype_col = \"celltypes\",\n",
    "                                    add_metrics=False)\n",
    "SU010_Total_Pre = import_query_data(path = 'data/BCC_samples/SU010_Total_Pre_vBCC',\n",
    "                                    mtx_file = 'matrix.mtx.gz',\n",
    "                                    cells_file = 'barcodes.tsv',\n",
    "                                    features_file = 'features.tsv.gz',\n",
    "                                    variable_prefix = \"SU010_Total_Pre\",\n",
    "                                    celltype_col = \"celltypes\",\n",
    "                                    add_metrics=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "0487470f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of query cells: 1737\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[View of AnnData object with n_obs × n_vars = 666 × 344492\n",
       "     obs: 'celltypes', 'tissue', 'dataset',\n",
       " View of AnnData object with n_obs × n_vars = 1071 × 344492\n",
       "     obs: 'celltypes', 'tissue', 'dataset']"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_list = [SU007_Total_Post, SU010_Total_Pre]\n",
    "print(\"Total number of query cells: {}\".format(np.sum([i.obs.shape[0] for i in data_list])))\n",
    "data_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "fa84e530",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SU010_Total_Pre#TACTGCCAGTTGAATG-1</th>\n",
       "      <td>SU010_Total_Pre#SU010_Total_Pre#TACTGCCAGTTGAA...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SU010_Total_Pre#AGCGATTAGAACTAAC-1</th>\n",
       "      <td>SU010_Total_Pre#SU010_Total_Pre#AGCGATTAGAACTA...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SU010_Total_Pre#GCCCGAAAGGCACCTC-1</th>\n",
       "      <td>SU010_Total_Pre#SU010_Total_Pre#GCCCGAAAGGCACC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SU010_Total_Pre#TCTCAGCCAGTTGGAG-1</th>\n",
       "      <td>SU010_Total_Pre#SU010_Total_Pre#TCTCAGCCAGTTGG...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SU010_Total_Pre#TATGTGGGTGAGGGTT-1</th>\n",
       "      <td>SU010_Total_Pre#SU010_Total_Pre#TATGTGGGTGAGGG...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                    0\n",
       "SU010_Total_Pre#TACTGCCAGTTGAATG-1  SU010_Total_Pre#SU010_Total_Pre#TACTGCCAGTTGAA...\n",
       "SU010_Total_Pre#AGCGATTAGAACTAAC-1  SU010_Total_Pre#SU010_Total_Pre#AGCGATTAGAACTA...\n",
       "SU010_Total_Pre#GCCCGAAAGGCACCTC-1  SU010_Total_Pre#SU010_Total_Pre#GCCCGAAAGGCACC...\n",
       "SU010_Total_Pre#TCTCAGCCAGTTGGAG-1  SU010_Total_Pre#SU010_Total_Pre#TCTCAGCCAGTTGG...\n",
       "SU010_Total_Pre#TATGTGGGTGAGGGTT-1  SU010_Total_Pre#SU010_Total_Pre#TATGTGGGTGAGGG..."
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "immune_cells.index = immune_cells[0]\n",
    "immune_cells.index = [i.split(\"_SU\")[0] for i in immune_cells.index]\n",
    "immune_cells.index = [i.split(\"#\")[1] + \"#\" + i.split(\"#\")[2] for i in immune_cells.index]\n",
    "immune_cells.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "0ad2a7d5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SU007_Total_Post\n",
      "View of AnnData object with n_obs × n_vars = 618 × 344492\n",
      "    obs: 'celltypes', 'tissue', 'dataset'\n",
      "SU010_Total_Pre\n",
      "View of AnnData object with n_obs × n_vars = 188 × 344492\n",
      "    obs: 'celltypes', 'tissue', 'dataset'\n",
      "Total immune cells: 806\n"
     ]
    }
   ],
   "source": [
    "data_list_use = data_list.copy()\n",
    "for i in range(len(data_list_use)):\n",
    "    print(data_list_use[i].obs[\"dataset\"][0])\n",
    "    data_list_use[i] = data_list_use[i][data_list_use[i].obs.index.isin(immune_cells.index)]\n",
    "    print(data_list_use[i])\n",
    "\n",
    "print(\"Total immune cells: {}\".format(np.sum([i.obs.shape[0] for i in data_list_use])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "762a6bc4",
   "metadata": {},
   "outputs": [],
   "source": [
    "reference_data.obs[\"CellType\"] = reference_data.obs[\"celltypes\"].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7f0c4fd9",
   "metadata": {},
   "outputs": [],
   "source": [
    "concat_adata = sc.AnnData.concatenate(reference_data, data_list_use[1])\n",
    "concat_adata = sc.AnnData.concatenate(concat_adata, data_list_use[0])\n",
    "\n",
    "Batch = [\"reference\"]*reference_data.shape[0] \\\n",
    "        + [\"SU010_Total_Pre\"]*data_list_use[1].shape[0] \\\n",
    "        + [\"SU007_Total_Post\"] * data_list_use[0].shape[0] \\\n",
    "        \n",
    "concat_adata.obs[\"Batch\"] = Batch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "f2156e28",
   "metadata": {},
   "outputs": [],
   "source": [
    "peaks = concat_adata.var_names.values\n",
    "\n",
    "chrom = [i.split(\":\")[0] for i in peaks]\n",
    "start = [i.split(\":\")[1].split(\"-\")[0] for i in peaks]\n",
    "end = [i.split(\":\")[1].split(\"-\")[1] for i in peaks]\n",
    "\n",
    "concat_adata = make_anndata(\n",
    "    adata = concat_adata, \n",
    "    chrom = chrom, \n",
    "    start = start, \n",
    "    end = end, \n",
    "    path = \"preprocessed_data/BCC_2_Cluster.h5ad\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05650fb5",
   "metadata": {},
   "source": [
    "Run CACNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "45d399b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "!python SANGO/CACNN/main.py -i preprocessed_data/BCC_2_Cluster.h5ad \\\n",
    "                -g hg38 \\\n",
    "                -o output/BCC_2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef6ace80",
   "metadata": {},
   "source": [
    "Run GraphTransformer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "61331c86",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "computing PCA\n",
      "    with n_comps=50\n",
      "    finished (0:00:00)\n",
      "computing batch balanced neighbors\n",
      "\tfinished: added to `.uns['neighbors']`\n",
      "\t`.obsp['distances']`, distances for each pair of neighbors\n",
      "\t`.obsp['connectivities']`, weighted adjacency matrix (0:00:03)\n",
      "running Leiden clustering\n",
      "    finished: found 13 clusters and added\n",
      "    'leiden', the cluster labels (adata.obs, categorical) (0:00:01)\n",
      "computing ridge regression\n",
      "\tfinished: `.X` now features regression residuals\n",
      "\t`.layers['X_explained']` stores the expression explained by the technical effect (0:00:00)\n",
      "computing PCA\n",
      "    with n_comps=50\n",
      "    finished (0:00:00)\n",
      "computing batch balanced neighbors\n",
      "\tfinished: added to `.uns['neighbors']`\n",
      "\t`.obsp['distances']`, distances for each pair of neighbors\n",
      "\t`.obsp['connectivities']`, weighted adjacency matrix (0:00:01)\n",
      "100%|█████████████████████████████████████████| 300/300 [02:43<00:00,  1.83it/s]\n"
     ]
    }
   ],
   "source": [
    "!python SANGO/GraphTransformer/main.py --data_dir output/BCC_2/CACNN_output.h5ad \\\n",
    "                --train_name_list reference --test_name SU010_Total_Pre SU007_Total_Post \\\n",
    "                --save_path output \\\n",
    "                --save_name BCC_2 \\\n",
    "                --save_unknown --save_rare --no_smote "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ce4043e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Atlas': AnnData object with n_obs × n_vars = 22008 × 344492\n",
       "     obs: 'celltypes', 'tissue', 'dataset', 'CellType'\n",
       "     var: 'selected'\n",
       "     uns: 'Group_colors', 'celltypes_colors', 'spectral_eigenvalue', 'true_label_colors'\n",
       "     obsm: 'X_spectral', 'X_umap',\n",
       " 'SU007_Total_Post': AnnData object with n_obs × n_vars = 618 × 344492\n",
       "     obs: 'celltypes', 'tissue', 'dataset'\n",
       "     var: 'selected',\n",
       " 'SU010_Total_Pre': AnnData object with n_obs × n_vars = 188 × 344492\n",
       "     obs: 'celltypes', 'tissue', 'dataset'\n",
       "     var: 'selected'}"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for anndata in data_list_use:\n",
    "    select_features(anndata)\n",
    "select_features(reference_data)\n",
    "\n",
    "datasets={}\n",
    "datasets[\"Atlas\"] = reference_data\n",
    "for anndata in data_list_use:\n",
    "    key = (anndata.obs[\"dataset\"])[0]\n",
    "    datasets[key] = anndata\n",
    "datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "3aba99e9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AnnData object with n_obs × n_vars = 22814 × 344492\n",
      "    obs: 'celltypes', 'tissue', 'dataset', 'CellType', 'pred_GraphTransformer', 'batch'\n",
      "    var: 'selected-0-0', 'selected-1-0', 'selected-1'\n",
      "    obsm: 'X'\n"
     ]
    }
   ],
   "source": [
    "adata = sc.read_h5ad(\"output/BCC_2/embedding.h5ad\")\n",
    "\n",
    "datasets[\"Atlas\"].obs[\"pred_GraphTransformer\"] = adata[adata.obs[\"Batch\"] == \"reference\"].obs[\"Pred\"].values\n",
    "datasets[\"SU010_Total_Pre\"].obs[\"pred_GraphTransformer\"] = adata[adata.obs[\"Batch\"] == \"SU010_Total_Pre\"].obs[\"Pred\"].values\n",
    "datasets[\"SU007_Total_Post\"].obs[\"pred_GraphTransformer\"] = adata[adata.obs[\"Batch\"] == \"SU007_Total_Post\"].obs[\"Pred\"].values\n",
    "\n",
    "datasets[\"Atlas\"].obsm[\"X\"] = adata[adata.obs[\"Batch\"] == \"reference\"].X\n",
    "datasets[\"SU010_Total_Pre\"].obsm[\"X\"] = adata[adata.obs[\"Batch\"] == \"SU010_Total_Pre\"].X\n",
    "datasets[\"SU007_Total_Post\"].obsm[\"X\"] = adata[adata.obs[\"Batch\"] == \"SU007_Total_Post\"].X\n",
    "\n",
    "integrated_adata = sc.AnnData.concatenate(datasets[\"Atlas\"], datasets[\"SU010_Total_Pre\"])\n",
    "integrated_adata = sc.AnnData.concatenate(integrated_adata, datasets[\"SU007_Total_Post\"])\n",
    "print(integrated_adata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "d2119758",
   "metadata": {},
   "outputs": [],
   "source": [
    "output_name = \"BCC_samples\"\n",
    "out_dir = os.path.join(\"case_study\", output_name)\n",
    "\n",
    "#Plot UMAP using spectral embeddings\n",
    "integrated_adata = get_umap(integrated_adata, out_dir, use_rep = \"X\", save = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "a44b8998",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = integrated_adata[integrated_adata.obs['dataset'] != \"reference\",:].copy()\n",
    "query.obs_names = [j+\"#\"+i.split(\"-\")[0] + \"-1\" + \"_\" + j for i,j in zip(query.obs_names.values, query.obs[\"dataset\"].values)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "b5bb13ba",
   "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>celltypes</th>\n",
       "      <th>tissue</th>\n",
       "      <th>dataset</th>\n",
       "      <th>CellType</th>\n",
       "      <th>pred_GraphTransformer</th>\n",
       "      <th>batch</th>\n",
       "      <th>UMAP_1</th>\n",
       "      <th>UMAP_2</th>\n",
       "      <th>Clusters</th>\n",
       "      <th>Group</th>\n",
       "      <th>depth</th>\n",
       "      <th>FRIP</th>\n",
       "      <th>Barcodes</th>\n",
       "      <th>Internal_Name</th>\n",
       "      <th>Group_Barcode</th>\n",
       "      <th>true_label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SU010_Total_Pre#SU010_Total_Pre#TACTGCCAGTTGAATG-1_SU010_Total_Pre</th>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Plasma B</td>\n",
       "      <td>0</td>\n",
       "      <td>-3.741690</td>\n",
       "      <td>16.458853</td>\n",
       "      <td>Cluster13</td>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>22180</td>\n",
       "      <td>0.629306</td>\n",
       "      <td>TACTGCCAGTTGAATG-1</td>\n",
       "      <td>SU010_Total_Pre_824</td>\n",
       "      <td>SU010_Total_Pre#TACTGCCAGTTGAATG-1</td>\n",
       "      <td>Plasma B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SU010_Total_Pre#SU010_Total_Pre#AGCGATTAGAACTAAC-1_SU010_Total_Pre</th>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Memory CD8 T</td>\n",
       "      <td>0</td>\n",
       "      <td>-5.042978</td>\n",
       "      <td>3.294526</td>\n",
       "      <td>Cluster7</td>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>26713</td>\n",
       "      <td>0.645416</td>\n",
       "      <td>AGCGATTAGAACTAAC-1</td>\n",
       "      <td>SU010_Total_Pre_4</td>\n",
       "      <td>SU010_Total_Pre#AGCGATTAGAACTAAC-1</td>\n",
       "      <td>Memory CD8 T</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SU010_Total_Pre#SU010_Total_Pre#GCCCGAAAGGCACCTC-1_SU010_Total_Pre</th>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Plasma B</td>\n",
       "      <td>0</td>\n",
       "      <td>-3.297045</td>\n",
       "      <td>16.337175</td>\n",
       "      <td>Cluster13</td>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>12510</td>\n",
       "      <td>0.385012</td>\n",
       "      <td>GCCCGAAAGGCACCTC-1</td>\n",
       "      <td>SU010_Total_Pre_843</td>\n",
       "      <td>SU010_Total_Pre#GCCCGAAAGGCACCTC-1</td>\n",
       "      <td>Plasma B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SU010_Total_Pre#SU010_Total_Pre#TCTCAGCCAGTTGGAG-1_SU010_Total_Pre</th>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Memory CD8 T</td>\n",
       "      <td>0</td>\n",
       "      <td>-5.287196</td>\n",
       "      <td>1.745298</td>\n",
       "      <td>Cluster7</td>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>26865</td>\n",
       "      <td>0.630430</td>\n",
       "      <td>TCTCAGCCAGTTGGAG-1</td>\n",
       "      <td>SU010_Total_Pre_77</td>\n",
       "      <td>SU010_Total_Pre#TCTCAGCCAGTTGGAG-1</td>\n",
       "      <td>Memory CD8 T</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SU010_Total_Pre#SU010_Total_Pre#TATGTGGGTGAGGGTT-1_SU010_Total_Pre</th>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Th1</td>\n",
       "      <td>0</td>\n",
       "      <td>-4.390906</td>\n",
       "      <td>1.357552</td>\n",
       "      <td>Cluster10</td>\n",
       "      <td>SU010_Total_Pre</td>\n",
       "      <td>14660</td>\n",
       "      <td>0.279775</td>\n",
       "      <td>TATGTGGGTGAGGGTT-1</td>\n",
       "      <td>SU010_Total_Pre_203</td>\n",
       "      <td>SU010_Total_Pre#TATGTGGGTGAGGGTT-1</td>\n",
       "      <td>NK1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SU007_Total_Post#SU007_Total_Post#GCACCTTCACTCGGAC-1_SU007_Total_Post</th>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Naive CD4 T</td>\n",
       "      <td>1</td>\n",
       "      <td>0.582895</td>\n",
       "      <td>0.034329</td>\n",
       "      <td>Cluster1</td>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>7646</td>\n",
       "      <td>0.669173</td>\n",
       "      <td>GCACCTTCACTCGGAC-1</td>\n",
       "      <td>SU007_Total_Post_657</td>\n",
       "      <td>SU007_Total_Post#GCACCTTCACTCGGAC-1</td>\n",
       "      <td>Naive CD4 T</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SU007_Total_Post#SU007_Total_Post#GCCTACTCATTCACGA-1_SU007_Total_Post</th>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Naive CD4 T</td>\n",
       "      <td>1</td>\n",
       "      <td>-2.006158</td>\n",
       "      <td>1.166633</td>\n",
       "      <td>Cluster5</td>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>2480</td>\n",
       "      <td>0.653629</td>\n",
       "      <td>GCCTACTCATTCACGA-1</td>\n",
       "      <td>SU007_Total_Post_628</td>\n",
       "      <td>SU007_Total_Post#GCCTACTCATTCACGA-1</td>\n",
       "      <td>Naive CD8 T</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SU007_Total_Post#SU007_Total_Post#AATGGAACAAGGTCGA-1_SU007_Total_Post</th>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Memory CD8 T</td>\n",
       "      <td>1</td>\n",
       "      <td>-5.390166</td>\n",
       "      <td>1.350978</td>\n",
       "      <td>Cluster7</td>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>4456</td>\n",
       "      <td>0.638241</td>\n",
       "      <td>AATGGAACAAGGTCGA-1</td>\n",
       "      <td>SU007_Total_Post_660</td>\n",
       "      <td>SU007_Total_Post#AATGGAACAAGGTCGA-1</td>\n",
       "      <td>Memory CD8 T</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SU007_Total_Post#SU007_Total_Post#TACCTATAGTACGACG-1_SU007_Total_Post</th>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Memory CD8 T</td>\n",
       "      <td>1</td>\n",
       "      <td>-4.832208</td>\n",
       "      <td>3.385367</td>\n",
       "      <td>Cluster7</td>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>3617</td>\n",
       "      <td>0.686342</td>\n",
       "      <td>TACCTATAGTACGACG-1</td>\n",
       "      <td>SU007_Total_Post_661</td>\n",
       "      <td>SU007_Total_Post#TACCTATAGTACGACG-1</td>\n",
       "      <td>Memory CD8 T</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SU007_Total_Post#SU007_Total_Post#TTCTGTAAGTACTCTG-1_SU007_Total_Post</th>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Memory CD8 T</td>\n",
       "      <td>1</td>\n",
       "      <td>-6.236699</td>\n",
       "      <td>4.539843</td>\n",
       "      <td>Cluster7</td>\n",
       "      <td>SU007_Total_Post</td>\n",
       "      <td>2556</td>\n",
       "      <td>0.699531</td>\n",
       "      <td>TTCTGTAAGTACTCTG-1</td>\n",
       "      <td>SU007_Total_Post_666</td>\n",
       "      <td>SU007_Total_Post#TTCTGTAAGTACTCTG-1</td>\n",
       "      <td>Memory CD8 T</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>806 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                           celltypes  \\\n",
       "SU010_Total_Pre#SU010_Total_Pre#TACTGCCAGTTGAAT...   SU010_Total_Pre   \n",
       "SU010_Total_Pre#SU010_Total_Pre#AGCGATTAGAACTAA...   SU010_Total_Pre   \n",
       "SU010_Total_Pre#SU010_Total_Pre#GCCCGAAAGGCACCT...   SU010_Total_Pre   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TCTCAGCCAGTTGGA...   SU010_Total_Pre   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TATGTGGGTGAGGGT...   SU010_Total_Pre   \n",
       "...                                                              ...   \n",
       "SU007_Total_Post#SU007_Total_Post#GCACCTTCACTCG...  SU007_Total_Post   \n",
       "SU007_Total_Post#SU007_Total_Post#GCCTACTCATTCA...  SU007_Total_Post   \n",
       "SU007_Total_Post#SU007_Total_Post#AATGGAACAAGGT...  SU007_Total_Post   \n",
       "SU007_Total_Post#SU007_Total_Post#TACCTATAGTACG...  SU007_Total_Post   \n",
       "SU007_Total_Post#SU007_Total_Post#TTCTGTAAGTACT...  SU007_Total_Post   \n",
       "\n",
       "                                                              tissue  \\\n",
       "SU010_Total_Pre#SU010_Total_Pre#TACTGCCAGTTGAAT...   SU010_Total_Pre   \n",
       "SU010_Total_Pre#SU010_Total_Pre#AGCGATTAGAACTAA...   SU010_Total_Pre   \n",
       "SU010_Total_Pre#SU010_Total_Pre#GCCCGAAAGGCACCT...   SU010_Total_Pre   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TCTCAGCCAGTTGGA...   SU010_Total_Pre   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TATGTGGGTGAGGGT...   SU010_Total_Pre   \n",
       "...                                                              ...   \n",
       "SU007_Total_Post#SU007_Total_Post#GCACCTTCACTCG...  SU007_Total_Post   \n",
       "SU007_Total_Post#SU007_Total_Post#GCCTACTCATTCA...  SU007_Total_Post   \n",
       "SU007_Total_Post#SU007_Total_Post#AATGGAACAAGGT...  SU007_Total_Post   \n",
       "SU007_Total_Post#SU007_Total_Post#TACCTATAGTACG...  SU007_Total_Post   \n",
       "SU007_Total_Post#SU007_Total_Post#TTCTGTAAGTACT...  SU007_Total_Post   \n",
       "\n",
       "                                                             dataset CellType  \\\n",
       "SU010_Total_Pre#SU010_Total_Pre#TACTGCCAGTTGAAT...   SU010_Total_Pre      NaN   \n",
       "SU010_Total_Pre#SU010_Total_Pre#AGCGATTAGAACTAA...   SU010_Total_Pre      NaN   \n",
       "SU010_Total_Pre#SU010_Total_Pre#GCCCGAAAGGCACCT...   SU010_Total_Pre      NaN   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TCTCAGCCAGTTGGA...   SU010_Total_Pre      NaN   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TATGTGGGTGAGGGT...   SU010_Total_Pre      NaN   \n",
       "...                                                              ...      ...   \n",
       "SU007_Total_Post#SU007_Total_Post#GCACCTTCACTCG...  SU007_Total_Post      NaN   \n",
       "SU007_Total_Post#SU007_Total_Post#GCCTACTCATTCA...  SU007_Total_Post      NaN   \n",
       "SU007_Total_Post#SU007_Total_Post#AATGGAACAAGGT...  SU007_Total_Post      NaN   \n",
       "SU007_Total_Post#SU007_Total_Post#TACCTATAGTACG...  SU007_Total_Post      NaN   \n",
       "SU007_Total_Post#SU007_Total_Post#TTCTGTAAGTACT...  SU007_Total_Post      NaN   \n",
       "\n",
       "                                                   pred_GraphTransformer  \\\n",
       "SU010_Total_Pre#SU010_Total_Pre#TACTGCCAGTTGAAT...              Plasma B   \n",
       "SU010_Total_Pre#SU010_Total_Pre#AGCGATTAGAACTAA...          Memory CD8 T   \n",
       "SU010_Total_Pre#SU010_Total_Pre#GCCCGAAAGGCACCT...              Plasma B   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TCTCAGCCAGTTGGA...          Memory CD8 T   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TATGTGGGTGAGGGT...                   Th1   \n",
       "...                                                                  ...   \n",
       "SU007_Total_Post#SU007_Total_Post#GCACCTTCACTCG...           Naive CD4 T   \n",
       "SU007_Total_Post#SU007_Total_Post#GCCTACTCATTCA...           Naive CD4 T   \n",
       "SU007_Total_Post#SU007_Total_Post#AATGGAACAAGGT...          Memory CD8 T   \n",
       "SU007_Total_Post#SU007_Total_Post#TACCTATAGTACG...          Memory CD8 T   \n",
       "SU007_Total_Post#SU007_Total_Post#TTCTGTAAGTACT...          Memory CD8 T   \n",
       "\n",
       "                                                   batch    UMAP_1     UMAP_2  \\\n",
       "SU010_Total_Pre#SU010_Total_Pre#TACTGCCAGTTGAAT...     0 -3.741690  16.458853   \n",
       "SU010_Total_Pre#SU010_Total_Pre#AGCGATTAGAACTAA...     0 -5.042978   3.294526   \n",
       "SU010_Total_Pre#SU010_Total_Pre#GCCCGAAAGGCACCT...     0 -3.297045  16.337175   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TCTCAGCCAGTTGGA...     0 -5.287196   1.745298   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TATGTGGGTGAGGGT...     0 -4.390906   1.357552   \n",
       "...                                                  ...       ...        ...   \n",
       "SU007_Total_Post#SU007_Total_Post#GCACCTTCACTCG...     1  0.582895   0.034329   \n",
       "SU007_Total_Post#SU007_Total_Post#GCCTACTCATTCA...     1 -2.006158   1.166633   \n",
       "SU007_Total_Post#SU007_Total_Post#AATGGAACAAGGT...     1 -5.390166   1.350978   \n",
       "SU007_Total_Post#SU007_Total_Post#TACCTATAGTACG...     1 -4.832208   3.385367   \n",
       "SU007_Total_Post#SU007_Total_Post#TTCTGTAAGTACT...     1 -6.236699   4.539843   \n",
       "\n",
       "                                                     Clusters  \\\n",
       "SU010_Total_Pre#SU010_Total_Pre#TACTGCCAGTTGAAT...  Cluster13   \n",
       "SU010_Total_Pre#SU010_Total_Pre#AGCGATTAGAACTAA...   Cluster7   \n",
       "SU010_Total_Pre#SU010_Total_Pre#GCCCGAAAGGCACCT...  Cluster13   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TCTCAGCCAGTTGGA...   Cluster7   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TATGTGGGTGAGGGT...  Cluster10   \n",
       "...                                                       ...   \n",
       "SU007_Total_Post#SU007_Total_Post#GCACCTTCACTCG...   Cluster1   \n",
       "SU007_Total_Post#SU007_Total_Post#GCCTACTCATTCA...   Cluster5   \n",
       "SU007_Total_Post#SU007_Total_Post#AATGGAACAAGGT...   Cluster7   \n",
       "SU007_Total_Post#SU007_Total_Post#TACCTATAGTACG...   Cluster7   \n",
       "SU007_Total_Post#SU007_Total_Post#TTCTGTAAGTACT...   Cluster7   \n",
       "\n",
       "                                                               Group  depth  \\\n",
       "SU010_Total_Pre#SU010_Total_Pre#TACTGCCAGTTGAAT...   SU010_Total_Pre  22180   \n",
       "SU010_Total_Pre#SU010_Total_Pre#AGCGATTAGAACTAA...   SU010_Total_Pre  26713   \n",
       "SU010_Total_Pre#SU010_Total_Pre#GCCCGAAAGGCACCT...   SU010_Total_Pre  12510   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TCTCAGCCAGTTGGA...   SU010_Total_Pre  26865   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TATGTGGGTGAGGGT...   SU010_Total_Pre  14660   \n",
       "...                                                              ...    ...   \n",
       "SU007_Total_Post#SU007_Total_Post#GCACCTTCACTCG...  SU007_Total_Post   7646   \n",
       "SU007_Total_Post#SU007_Total_Post#GCCTACTCATTCA...  SU007_Total_Post   2480   \n",
       "SU007_Total_Post#SU007_Total_Post#AATGGAACAAGGT...  SU007_Total_Post   4456   \n",
       "SU007_Total_Post#SU007_Total_Post#TACCTATAGTACG...  SU007_Total_Post   3617   \n",
       "SU007_Total_Post#SU007_Total_Post#TTCTGTAAGTACT...  SU007_Total_Post   2556   \n",
       "\n",
       "                                                        FRIP  \\\n",
       "SU010_Total_Pre#SU010_Total_Pre#TACTGCCAGTTGAAT...  0.629306   \n",
       "SU010_Total_Pre#SU010_Total_Pre#AGCGATTAGAACTAA...  0.645416   \n",
       "SU010_Total_Pre#SU010_Total_Pre#GCCCGAAAGGCACCT...  0.385012   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TCTCAGCCAGTTGGA...  0.630430   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TATGTGGGTGAGGGT...  0.279775   \n",
       "...                                                      ...   \n",
       "SU007_Total_Post#SU007_Total_Post#GCACCTTCACTCG...  0.669173   \n",
       "SU007_Total_Post#SU007_Total_Post#GCCTACTCATTCA...  0.653629   \n",
       "SU007_Total_Post#SU007_Total_Post#AATGGAACAAGGT...  0.638241   \n",
       "SU007_Total_Post#SU007_Total_Post#TACCTATAGTACG...  0.686342   \n",
       "SU007_Total_Post#SU007_Total_Post#TTCTGTAAGTACT...  0.699531   \n",
       "\n",
       "                                                              Barcodes  \\\n",
       "SU010_Total_Pre#SU010_Total_Pre#TACTGCCAGTTGAAT...  TACTGCCAGTTGAATG-1   \n",
       "SU010_Total_Pre#SU010_Total_Pre#AGCGATTAGAACTAA...  AGCGATTAGAACTAAC-1   \n",
       "SU010_Total_Pre#SU010_Total_Pre#GCCCGAAAGGCACCT...  GCCCGAAAGGCACCTC-1   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TCTCAGCCAGTTGGA...  TCTCAGCCAGTTGGAG-1   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TATGTGGGTGAGGGT...  TATGTGGGTGAGGGTT-1   \n",
       "...                                                                ...   \n",
       "SU007_Total_Post#SU007_Total_Post#GCACCTTCACTCG...  GCACCTTCACTCGGAC-1   \n",
       "SU007_Total_Post#SU007_Total_Post#GCCTACTCATTCA...  GCCTACTCATTCACGA-1   \n",
       "SU007_Total_Post#SU007_Total_Post#AATGGAACAAGGT...  AATGGAACAAGGTCGA-1   \n",
       "SU007_Total_Post#SU007_Total_Post#TACCTATAGTACG...  TACCTATAGTACGACG-1   \n",
       "SU007_Total_Post#SU007_Total_Post#TTCTGTAAGTACT...  TTCTGTAAGTACTCTG-1   \n",
       "\n",
       "                                                           Internal_Name  \\\n",
       "SU010_Total_Pre#SU010_Total_Pre#TACTGCCAGTTGAAT...   SU010_Total_Pre_824   \n",
       "SU010_Total_Pre#SU010_Total_Pre#AGCGATTAGAACTAA...     SU010_Total_Pre_4   \n",
       "SU010_Total_Pre#SU010_Total_Pre#GCCCGAAAGGCACCT...   SU010_Total_Pre_843   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TCTCAGCCAGTTGGA...    SU010_Total_Pre_77   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TATGTGGGTGAGGGT...   SU010_Total_Pre_203   \n",
       "...                                                                  ...   \n",
       "SU007_Total_Post#SU007_Total_Post#GCACCTTCACTCG...  SU007_Total_Post_657   \n",
       "SU007_Total_Post#SU007_Total_Post#GCCTACTCATTCA...  SU007_Total_Post_628   \n",
       "SU007_Total_Post#SU007_Total_Post#AATGGAACAAGGT...  SU007_Total_Post_660   \n",
       "SU007_Total_Post#SU007_Total_Post#TACCTATAGTACG...  SU007_Total_Post_661   \n",
       "SU007_Total_Post#SU007_Total_Post#TTCTGTAAGTACT...  SU007_Total_Post_666   \n",
       "\n",
       "                                                                          Group_Barcode  \\\n",
       "SU010_Total_Pre#SU010_Total_Pre#TACTGCCAGTTGAAT...   SU010_Total_Pre#TACTGCCAGTTGAATG-1   \n",
       "SU010_Total_Pre#SU010_Total_Pre#AGCGATTAGAACTAA...   SU010_Total_Pre#AGCGATTAGAACTAAC-1   \n",
       "SU010_Total_Pre#SU010_Total_Pre#GCCCGAAAGGCACCT...   SU010_Total_Pre#GCCCGAAAGGCACCTC-1   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TCTCAGCCAGTTGGA...   SU010_Total_Pre#TCTCAGCCAGTTGGAG-1   \n",
       "SU010_Total_Pre#SU010_Total_Pre#TATGTGGGTGAGGGT...   SU010_Total_Pre#TATGTGGGTGAGGGTT-1   \n",
       "...                                                                                 ...   \n",
       "SU007_Total_Post#SU007_Total_Post#GCACCTTCACTCG...  SU007_Total_Post#GCACCTTCACTCGGAC-1   \n",
       "SU007_Total_Post#SU007_Total_Post#GCCTACTCATTCA...  SU007_Total_Post#GCCTACTCATTCACGA-1   \n",
       "SU007_Total_Post#SU007_Total_Post#AATGGAACAAGGT...  SU007_Total_Post#AATGGAACAAGGTCGA-1   \n",
       "SU007_Total_Post#SU007_Total_Post#TACCTATAGTACG...  SU007_Total_Post#TACCTATAGTACGACG-1   \n",
       "SU007_Total_Post#SU007_Total_Post#TTCTGTAAGTACT...  SU007_Total_Post#TTCTGTAAGTACTCTG-1   \n",
       "\n",
       "                                                      true_label  \n",
       "SU010_Total_Pre#SU010_Total_Pre#TACTGCCAGTTGAAT...      Plasma B  \n",
       "SU010_Total_Pre#SU010_Total_Pre#AGCGATTAGAACTAA...  Memory CD8 T  \n",
       "SU010_Total_Pre#SU010_Total_Pre#GCCCGAAAGGCACCT...      Plasma B  \n",
       "SU010_Total_Pre#SU010_Total_Pre#TCTCAGCCAGTTGGA...  Memory CD8 T  \n",
       "SU010_Total_Pre#SU010_Total_Pre#TATGTGGGTGAGGGT...           NK1  \n",
       "...                                                          ...  \n",
       "SU007_Total_Post#SU007_Total_Post#GCACCTTCACTCG...   Naive CD4 T  \n",
       "SU007_Total_Post#SU007_Total_Post#GCCTACTCATTCA...   Naive CD8 T  \n",
       "SU007_Total_Post#SU007_Total_Post#AATGGAACAAGGT...  Memory CD8 T  \n",
       "SU007_Total_Post#SU007_Total_Post#TACCTATAGTACG...  Memory CD8 T  \n",
       "SU007_Total_Post#SU007_Total_Post#TTCTGTAAGTACT...  Memory CD8 T  \n",
       "\n",
       "[806 rows x 16 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "projection_allcells = pd.read_table(\"data/BCC_samples/BCC_study_metadata.csv\", index_col = 0, sep = \",\")\n",
    "projection_allcells.index = [projection_allcells.loc[i,\"Group\"] + \"#\" + i for i in projection_allcells.index]\n",
    "projection_allcells[\"true_label\"] = [i.strip() for i in projection_allcells[\"true_label\"]]\n",
    "sample_names = [\"SU010_Total_Pre\", \"SU007_Total_Post\"]\n",
    "projection = projection_allcells[projection_allcells[\"Group\"].isin(sample_names)]\n",
    "query.obs = pd.merge(query.obs, projection, left_index=True, right_index=True)\n",
    "query.obs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "174a3f2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "query.obsm[\"X_umap\"] = np.array(query.obs[[\"UMAP_1\", \"UMAP_2\"]])\n",
    "query.obs[\"pred_y_unknown\"] = np.array(query.obs[\"pred_GraphTransformer\"].values)\n",
    "query_annotated = cluster_assign(query, use_rep = \"X\", cluster_col = \"Clusters\", UMAP=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "91b39e30",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 7680x5760 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(dpi=1200)\n",
    "sc.pl.umap(query_annotated, color = \"cluster_annotation\", title=\"\", legend_loc = \"on data\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "9e88d049",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 7680x5760 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pred_col = 'cluster_annotation'\n",
    "true_col = 'true_label'\n",
    "\n",
    "plt.rcParams['font.weight'] = \"heavy\"\n",
    "plt.figure(dpi=1200)\n",
    "sankey(\n",
    "    query_annotated.obs[pred_col], query_annotated.obs[true_col], aspect=10,\n",
    "    fontsize=10\n",
    "    )"
   ]
  }
 ],
 "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": "3.8.17"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}