lung_ingest.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>.container { width:95% !important; }</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import scvelo as scv\n",
    "from IPython.display import clear_output\n",
    "import matplotlib.backends.backend_pdf\n",
    "from tqdm.notebook import tqdm\n",
    "import scanpy as sc\n",
    "import matplotlib.pyplot as pl\n",
    "import anndata as ad\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scanpy.external as sce\n",
    "from IPython.core.display import display, HTML\n",
    "display(HTML(\"<style>.container { width:95% !important; }</style>\"))\n",
    "%matplotlib inline\n",
    "scv.settings.verbosity=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "kim_data_str = sc.read(\"/fast/users/bischofp_c/scratch/data/Lung/kim_str_new_annotation.h5ad\")\n",
    "kim_data_imm = sc.read(\"/fast/users/bischofp_c/scratch/data/Lung/kim_imm_new_annotation.h5ad\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 5291 × 3000\n",
       "    obs: 'orig.ident', 'nCount_RNA', 'nFeature_RNA', 'pMT', 'pHB', 'nCount_SCT', 'nFeature_SCT', 'Index', 'Barcode', 'Sample', 'Sample_Origin', 'Cell_type', 'Cell_type.refined', 'Cell_subtype', 'S.Score', 'G2M.Score', 'Phase', 'CC.Diff', 'cell_id', 'No', 'Patient.id', 'Samples', 'Tissue.origins', 'Histology', 'Sex', 'Age', 'Smoking', 'Pathology', 'EGFR', 'Stages', 'No..of.single.cells', 'SCT_snn_res.0.2', 'seurat_clusters', 'SCT_snn_res.0.3', 'SCT_snn_res.0.4', 'SCT_snn_res.0.5', 'SCT_snn_res.1', 'SCT_snn_res.2', 'main_cell_type'\n",
       "    var: 'sct.detection_rate', 'sct.gmean', 'sct.variance', 'sct.residual_variance', 'sct.variable'\n",
       "    obsm: 'X_pca', 'X_umap'\n",
       "    varm: 'PCs'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kim_data_str"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 70570 × 3000\n",
       "    obs: 'orig.ident', 'nCount_RNA', 'nFeature_RNA', 'pMT', 'pHB', 'nCount_SCT', 'nFeature_SCT', 'Index', 'Barcode', 'Sample', 'Sample_Origin', 'Cell_type', 'Cell_type.refined', 'Cell_subtype', 'S.Score', 'G2M.Score', 'Phase', 'CC.Diff', 'cell_id', 'No', 'Patient.id', 'Samples', 'Tissue.origins', 'Histology', 'Sex', 'Age', 'Smoking', 'Pathology', 'EGFR', 'Stages', 'No..of.single.cells', 'SCT_snn_res.0.2', 'seurat_clusters', 'SCT_snn_res.0.3', 'SCT_snn_res.0.4', 'SCT_snn_res.0.5', 'SCT_snn_res.1', 'SCT_snn_res.2', 'main_cell_type'\n",
       "    var: 'sct.detection_rate', 'sct.gmean', 'sct.variance', 'sct.residual_variance', 'sct.variable'\n",
       "    obsm: 'X_pca', 'X_umap'\n",
       "    varm: 'PCs'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kim_data_imm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "our_data_str = sc.read(\"/fast/users/bischofp_c/scratch/data/Lung/str_anno.h5ad\")\n",
    "our_data_imm = sc.read(\"/fast/users/bischofp_c/scratch/data/Lung/imm_anno.h5ad\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 3899 × 3000\n",
       "    obs: 'orig.ident', 'nCount_RNA', 'nFeature_RNA', 'pMT', 'pHB', 'pRP', 'nCount_SCT', 'nFeature_SCT', 'SCT_snn_res.0.2', 'seurat_clusters', 'SCT_snn_res.0.3', 'SCT_snn_res.0.4', 'SCT_snn_res.0.5', 'SCT_snn_res.1', 'SCT_snn_res.2', 'main_cell_type', 'cell_id', 'sample_id', 'patient_id', 'tissue_type', 'W_no', 'date_of_surgery', 'topography', 'morphology', 'histo_subtype', 'tnm', 'sex', 'age', 'frozen', 'ffpe', 'S.Score', 'G2M.Score', 'Phase', 'CC.Diff', 'T_Club1', 'T_Ciliated2', 'T_Proximal.Ciliated3', 'T_Basal4', 'T_Proximal.Basal5', 'T_Differentiating.Basal6', 'T_Proliferating.Basal7', 'T_Goblet8', 'T_Mucous9', 'T_Serous10', 'T_Ionocyte11', 'T_Neuroendocrine12', 'T_Alveolar.Epithelial.Type.113', 'T_Alveolar.Epithelial.Type.214', 'T_Signaling.Alveolar.Epithelial.Type.215', 'T_Artery16', 'T_Vein17', 'T_Capillary.Aerocyte18', 'T_Capillary19', 'T_Capillary.Intermediate.120', 'T_Capillary.Intermediate.221', 'T_Bronchial.Vessel.122', 'T_Bronchial.Vessel.223', 'T_Lymphatics24', 'T_Airway.Smooth.Muscle25', 'T_Vascular.Smooth.Muscle26', 'T_Myofibroblast27', 'T_Fibromyocyte28', 'T_Adventitial.Fibroblast29', 'T_Alveolar.Fibroblast30', 'T_Lipofibroblast31', 'T_Pericyte32', 'T_Mesothelial33', 'T_B34', 'T_Plasma35', 'T_CD8..Memory.Effector.T36', 'T_CD8..Naive.T37', 'T_CD4..Memory.Effector.T38', 'T_CD4..Naive.T39', 'T_Natural.Killer.T40', 'T_Natural.Killer41', 'T_Proliferating.NK.T42', 'T_Mast.Cell.Basophil.Type.143', 'T_Mast.Cell.Basophil.Type.244', 'T_Platelet.Megakaryocyte45', 'T_Macrophage46', 'T_Proliferating.Macrophage47', 'T_Plasmacytoid.Dendritic48', 'T_Myeloid.Dendritic.Type.149', 'T_Myeloid.Dendritic.Type.250', 'T_IGSF21..Dendritic51', 'T_EREG..Dendritic52', 'T_TREM2..Dendritic53', 'T_Classical.Monocyte54', 'T_OLR1..Classical.Monocyte55', 'T_Nonclassical.Monocyte56', 'T_Intermediate.Monocyte57', 'VB_Basal.11', 'VB_Basal.22', 'VB_Ciliated.13', 'VB_Ciliated.24', 'VB_Club5', 'VB_Goblet.26', 'VB_Goblet.17', 'VB_Ionocytes8', 'VB_Type.2.alveolar9', 'VB_Type.1.alveolar10', 'VB_B.cells11', 'VB_Dendritic.cells12', 'VB_Endothelial13', 'VB_Fibroblasts14', 'VB_Luminal.Macrophages15', 'VB_Lymphatic16', 'VB_Mast.cells17', 'VB_Mesothelium18', 'VB_Neutrophils19', 'VB_Smooth.muscle20', 'VB_T.and.NK21', 'cell_type_str', 'HALLMARK_TNFA_SIGNALING_VIA_NFKB1', 'HALLMARK_HYPOXIA2', 'HALLMARK_CHOLESTEROL_HOMEOSTASIS3', 'HALLMARK_MITOTIC_SPINDLE4', 'HALLMARK_WNT_BETA_CATENIN_SIGNALING5', 'HALLMARK_TGF_BETA_SIGNALING6', 'HALLMARK_IL6_JAK_STAT3_SIGNALING7', 'HALLMARK_DNA_REPAIR8', 'HALLMARK_G2M_CHECKPOINT9', 'HALLMARK_APOPTOSIS10', 'HALLMARK_NOTCH_SIGNALING11', 'HALLMARK_ADIPOGENESIS12', 'HALLMARK_ESTROGEN_RESPONSE_EARLY13', 'HALLMARK_ESTROGEN_RESPONSE_LATE14', 'HALLMARK_ANDROGEN_RESPONSE15', 'HALLMARK_MYOGENESIS16', 'HALLMARK_PROTEIN_SECRETION17', 'HALLMARK_INTERFERON_ALPHA_RESPONSE18', 'HALLMARK_INTERFERON_GAMMA_RESPONSE19', 'HALLMARK_APICAL_JUNCTION20', 'HALLMARK_APICAL_SURFACE21', 'HALLMARK_HEDGEHOG_SIGNALING22', 'HALLMARK_COMPLEMENT23', 'HALLMARK_UNFOLDED_PROTEIN_RESPONSE24', 'HALLMARK_PI3K_AKT_MTOR_SIGNALING25', 'HALLMARK_MTORC1_SIGNALING26', 'HALLMARK_E2F_TARGETS27', 'HALLMARK_MYC_TARGETS_V128', 'HALLMARK_MYC_TARGETS_V229', 'HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION30', 'HALLMARK_INFLAMMATORY_RESPONSE31', 'HALLMARK_XENOBIOTIC_METABOLISM32', 'HALLMARK_FATTY_ACID_METABOLISM33', 'HALLMARK_OXIDATIVE_PHOSPHORYLATION34', 'HALLMARK_GLYCOLYSIS35', 'HALLMARK_REACTIVE_OXIGEN_SPECIES_PATHWAY36', 'HALLMARK_P53_PATHWAY37', 'HALLMARK_UV_RESPONSE_UP38', 'HALLMARK_UV_RESPONSE_DN39', 'HALLMARK_ANGIOGENESIS40', 'HALLMARK_HEME_METABOLISM41', 'HALLMARK_COAGULATION42', 'HALLMARK_IL2_STAT5_SIGNALING43', 'HALLMARK_BILE_ACID_METABOLISM44', 'HALLMARK_PEROXISOME45', 'HALLMARK_ALLOGRAFT_REJECTION46', 'HALLMARK_SPERMATOGENESIS47', 'HALLMARK_KRAS_SIGNALING_UP48', 'HALLMARK_KRAS_SIGNALING_DN49', 'HALLMARK_PANCREAS_BETA_CELLS50'\n",
       "    var: 'sct.detection_rate', 'sct.gmean', 'sct.variance', 'sct.residual_variance', 'sct.variable'\n",
       "    obsm: 'X_pca', 'X_umap'\n",
       "    varm: 'PCs'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "our_data_str"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 88956 × 3000\n",
       "    obs: 'orig.ident', 'nCount_RNA', 'nFeature_RNA', 'pMT', 'pHB', 'pRP', 'nCount_SCT', 'nFeature_SCT', 'SCT_snn_res.0.2', 'seurat_clusters', 'SCT_snn_res.0.3', 'SCT_snn_res.0.4', 'SCT_snn_res.0.5', 'SCT_snn_res.1', 'SCT_snn_res.2', 'main_cell_type', 'cell_id', 'sample_id', 'patient_id', 'tissue_type', 'W_no', 'date_of_surgery', 'topography', 'morphology', 'histo_subtype', 'tnm', 'sex', 'age', 'frozen', 'ffpe', 'S.Score', 'G2M.Score', 'Phase', 'CC.Diff', 'T_Club1', 'T_Ciliated2', 'T_Proximal.Ciliated3', 'T_Basal4', 'T_Proximal.Basal5', 'T_Differentiating.Basal6', 'T_Proliferating.Basal7', 'T_Goblet8', 'T_Mucous9', 'T_Serous10', 'T_Ionocyte11', 'T_Neuroendocrine12', 'T_Alveolar.Epithelial.Type.113', 'T_Alveolar.Epithelial.Type.214', 'T_Signaling.Alveolar.Epithelial.Type.215', 'T_Artery16', 'T_Vein17', 'T_Capillary.Aerocyte18', 'T_Capillary19', 'T_Capillary.Intermediate.120', 'T_Capillary.Intermediate.221', 'T_Bronchial.Vessel.122', 'T_Bronchial.Vessel.223', 'T_Lymphatics24', 'T_Airway.Smooth.Muscle25', 'T_Vascular.Smooth.Muscle26', 'T_Myofibroblast27', 'T_Fibromyocyte28', 'T_Adventitial.Fibroblast29', 'T_Alveolar.Fibroblast30', 'T_Lipofibroblast31', 'T_Pericyte32', 'T_Mesothelial33', 'T_B34', 'T_Plasma35', 'T_CD8..Memory.Effector.T36', 'T_CD8..Naive.T37', 'T_CD4..Memory.Effector.T38', 'T_CD4..Naive.T39', 'T_Natural.Killer.T40', 'T_Natural.Killer41', 'T_Proliferating.NK.T42', 'T_Mast.Cell.Basophil.Type.143', 'T_Mast.Cell.Basophil.Type.244', 'T_Platelet.Megakaryocyte45', 'T_Macrophage46', 'T_Proliferating.Macrophage47', 'T_Plasmacytoid.Dendritic48', 'T_Myeloid.Dendritic.Type.149', 'T_Myeloid.Dendritic.Type.250', 'T_IGSF21..Dendritic51', 'T_EREG..Dendritic52', 'T_TREM2..Dendritic53', 'T_Classical.Monocyte54', 'T_OLR1..Classical.Monocyte55', 'T_Nonclassical.Monocyte56', 'T_Intermediate.Monocyte57', 'VB_Basal.11', 'VB_Basal.22', 'VB_Ciliated.13', 'VB_Ciliated.24', 'VB_Club5', 'VB_Goblet.26', 'VB_Goblet.17', 'VB_Ionocytes8', 'VB_Type.2.alveolar9', 'VB_Type.1.alveolar10', 'VB_B.cells11', 'VB_Dendritic.cells12', 'VB_Endothelial13', 'VB_Fibroblasts14', 'VB_Luminal.Macrophages15', 'VB_Lymphatic16', 'VB_Mast.cells17', 'VB_Mesothelium18', 'VB_Neutrophils19', 'VB_Smooth.muscle20', 'VB_T.and.NK21', 'cell_type_imm', 'HALLMARK_TNFA_SIGNALING_VIA_NFKB1', 'HALLMARK_HYPOXIA2', 'HALLMARK_CHOLESTEROL_HOMEOSTASIS3', 'HALLMARK_MITOTIC_SPINDLE4', 'HALLMARK_WNT_BETA_CATENIN_SIGNALING5', 'HALLMARK_TGF_BETA_SIGNALING6', 'HALLMARK_IL6_JAK_STAT3_SIGNALING7', 'HALLMARK_DNA_REPAIR8', 'HALLMARK_G2M_CHECKPOINT9', 'HALLMARK_APOPTOSIS10', 'HALLMARK_NOTCH_SIGNALING11', 'HALLMARK_ADIPOGENESIS12', 'HALLMARK_ESTROGEN_RESPONSE_EARLY13', 'HALLMARK_ESTROGEN_RESPONSE_LATE14', 'HALLMARK_ANDROGEN_RESPONSE15', 'HALLMARK_MYOGENESIS16', 'HALLMARK_PROTEIN_SECRETION17', 'HALLMARK_INTERFERON_ALPHA_RESPONSE18', 'HALLMARK_INTERFERON_GAMMA_RESPONSE19', 'HALLMARK_APICAL_JUNCTION20', 'HALLMARK_APICAL_SURFACE21', 'HALLMARK_HEDGEHOG_SIGNALING22', 'HALLMARK_COMPLEMENT23', 'HALLMARK_UNFOLDED_PROTEIN_RESPONSE24', 'HALLMARK_PI3K_AKT_MTOR_SIGNALING25', 'HALLMARK_MTORC1_SIGNALING26', 'HALLMARK_E2F_TARGETS27', 'HALLMARK_MYC_TARGETS_V128', 'HALLMARK_MYC_TARGETS_V229', 'HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION30', 'HALLMARK_INFLAMMATORY_RESPONSE31', 'HALLMARK_XENOBIOTIC_METABOLISM32', 'HALLMARK_FATTY_ACID_METABOLISM33', 'HALLMARK_OXIDATIVE_PHOSPHORYLATION34', 'HALLMARK_GLYCOLYSIS35', 'HALLMARK_REACTIVE_OXIGEN_SPECIES_PATHWAY36', 'HALLMARK_P53_PATHWAY37', 'HALLMARK_UV_RESPONSE_UP38', 'HALLMARK_UV_RESPONSE_DN39', 'HALLMARK_ANGIOGENESIS40', 'HALLMARK_HEME_METABOLISM41', 'HALLMARK_COAGULATION42', 'HALLMARK_IL2_STAT5_SIGNALING43', 'HALLMARK_BILE_ACID_METABOLISM44', 'HALLMARK_PEROXISOME45', 'HALLMARK_ALLOGRAFT_REJECTION46', 'HALLMARK_SPERMATOGENESIS47', 'HALLMARK_KRAS_SIGNALING_UP48', 'HALLMARK_KRAS_SIGNALING_DN49', 'HALLMARK_PANCREAS_BETA_CELLS50'\n",
       "    var: 'sct.detection_rate', 'sct.gmean', 'sct.variance', 'sct.residual_variance', 'sct.variable'\n",
       "    obsm: 'X_pca', 'X_umap'\n",
       "    varm: 'PCs'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "our_data_imm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "var_names_str = our_data_str.var_names.intersection(kim_data_str.var_names)\n",
    "our_data_str = our_data_str[:, var_names_str]\n",
    "kim_data_str = kim_data_str[:, var_names_str]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "var_names_imm = our_data_imm.var_names.intersection(kim_data_imm.var_names)\n",
    "our_data_imm = our_data_imm[:, var_names_imm]\n",
    "kim_data_imm = kim_data_imm[:, var_names_imm]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "sc.pp.pca(our_data_str)\n",
    "sc.pp.neighbors(our_data_str)\n",
    "our_data_str.uns['umap'] = {'params': {'a': 0.583030019901822, 'b': 1.3341669931033755}}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.pp.pca(our_data_imm)\n",
    "sc.pp.neighbors(our_data_imm)\n",
    "our_data_imm.uns['umap'] = {'params': {'a': 0.583030019901822, 'b': 1.3341669931033755}}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "mapped_kim_data_str = sc.tl.ingest(kim_data_str, our_data_str, obs='cell_type_str', inplace=False)\n",
    "mapped_kim_data_imm = sc.tl.ingest(kim_data_imm, our_data_imm, obs='cell_type_imm', inplace=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 5291 × 1890\n",
       "    obs: 'orig.ident', 'nCount_RNA', 'nFeature_RNA', 'pMT', 'pHB', 'nCount_SCT', 'nFeature_SCT', 'Index', 'Barcode', 'Sample', 'Sample_Origin', 'Cell_type', 'Cell_type.refined', 'Cell_subtype', 'S.Score', 'G2M.Score', 'Phase', 'CC.Diff', 'cell_id', 'No', 'Patient.id', 'Samples', 'Tissue.origins', 'Histology', 'Sex', 'Age', 'Smoking', 'Pathology', 'EGFR', 'Stages', 'No..of.single.cells', 'SCT_snn_res.0.2', 'seurat_clusters', 'SCT_snn_res.0.3', 'SCT_snn_res.0.4', 'SCT_snn_res.0.5', 'SCT_snn_res.1', 'SCT_snn_res.2', 'main_cell_type', 'cell_type_str'\n",
       "    var: 'sct.detection_rate', 'sct.gmean', 'sct.variance', 'sct.residual_variance', 'sct.variable'\n",
       "    obsm: 'X_pca', 'X_umap', 'rep'\n",
       "    varm: 'PCs'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mapped_kim_data_str"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 70570 × 1890\n",
       "    obs: 'orig.ident', 'nCount_RNA', 'nFeature_RNA', 'pMT', 'pHB', 'nCount_SCT', 'nFeature_SCT', 'Index', 'Barcode', 'Sample', 'Sample_Origin', 'Cell_type', 'Cell_type.refined', 'Cell_subtype', 'S.Score', 'G2M.Score', 'Phase', 'CC.Diff', 'cell_id', 'No', 'Patient.id', 'Samples', 'Tissue.origins', 'Histology', 'Sex', 'Age', 'Smoking', 'Pathology', 'EGFR', 'Stages', 'No..of.single.cells', 'SCT_snn_res.0.2', 'seurat_clusters', 'SCT_snn_res.0.3', 'SCT_snn_res.0.4', 'SCT_snn_res.0.5', 'SCT_snn_res.1', 'SCT_snn_res.2', 'main_cell_type', 'cell_type_imm'\n",
       "    var: 'sct.detection_rate', 'sct.gmean', 'sct.variance', 'sct.residual_variance', 'sct.variable'\n",
       "    obsm: 'X_pca', 'X_umap', 'rep'\n",
       "    varm: 'PCs'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mapped_kim_data_imm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "writing .csv files to /fast/users/bischofp_c/scratch/data/Lung/mapped_kim_str\n"
     ]
    }
   ],
   "source": [
    "mapped_kim_data_str.write_csvs('/fast/users/bischofp_c/scratch/data/Lung/mapped_kim_str')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "writing .csv files to /fast/users/bischofp_c/scratch/data/Lung/mapped_kim_imm\n"
     ]
    }
   ],
   "source": [
    "mapped_kim_data_imm.write_csvs('/fast/users/bischofp_c/scratch/data/Lung/mapped_kim_imm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alabaster==0.7.12\n",
      "anaconda-client==1.7.2\n",
      "anaconda-navigator==1.9.12\n",
      "anaconda-project==0.8.3\n",
      "anndata==0.7.5\n",
      "argh==0.26.2\n",
      "asn1crypto==1.3.0\n",
      "astroid==2.3.3\n",
      "astropy==4.0\n",
      "atomicwrites==1.3.0\n",
      "attrs==19.3.0\n",
      "autopep8==1.4.4\n",
      "Babel==2.8.0\n",
      "backcall==0.1.0\n",
      "backports.functools-lru-cache==1.6.1\n",
      "backports.shutil-get-terminal-size==1.0.0\n",
      "backports.tempfile==1.0\n",
      "backports.weakref==1.0.post1\n",
      "bash-kernel==0.7.2\n",
      "beautifulsoup4==4.8.2\n",
      "bitarray==1.2.1\n",
      "bkcharts==0.2\n",
      "bleach==3.1.0\n",
      "bokeh==1.4.0\n",
      "boto==2.49.0\n",
      "Bottleneck==1.3.2\n",
      "certifi==2019.11.28\n",
      "cffi==1.14.0\n",
      "chardet==3.0.4\n",
      "Click==7.0\n",
      "cloudpickle==1.3.0\n",
      "clyent==1.2.2\n",
      "colorama==0.4.3\n",
      "conda==4.8.3\n",
      "conda-build==3.18.11\n",
      "conda-package-handling==1.6.0\n",
      "conda-verify==3.4.2\n",
      "contextlib2==0.6.0.post1\n",
      "cryptography==2.8\n",
      "cycler==0.10.0\n",
      "Cython==0.29.15\n",
      "cytoolz==0.10.1\n",
      "dask==2.11.0\n",
      "decorator==4.4.1\n",
      "defusedxml==0.6.0\n",
      "diff-match-patch==20181111\n",
      "distributed==2.11.0\n",
      "docutils==0.16\n",
      "entrypoints==0.3\n",
      "et-xmlfile==1.0.1\n",
      "fastcache==1.1.0\n",
      "filelock==3.0.12\n",
      "flake8==3.7.9\n",
      "Flask==1.1.1\n",
      "fsspec==0.6.2\n",
      "future==0.18.2\n",
      "get-version==2.1\n",
      "gevent==1.4.0\n",
      "glob2==0.7\n",
      "gmpy2==2.0.8\n",
      "greenlet==0.4.15\n",
      "h5py==2.10.0\n",
      "HeapDict==1.0.1\n",
      "html5lib==1.0.1\n",
      "hypothesis==5.5.4\n",
      "idna==2.8\n",
      "imageio==2.6.1\n",
      "imagesize==1.2.0\n",
      "importlib-metadata==1.5.0\n",
      "intervaltree==3.0.2\n",
      "ipykernel==5.1.4\n",
      "ipython==7.12.0\n",
      "ipython-genutils==0.2.0\n",
      "ipywidgets==7.5.1\n",
      "isort==4.3.21\n",
      "itsdangerous==1.1.0\n",
      "jdcal==1.4.1\n",
      "jedi==0.14.1\n",
      "jeepney==0.4.2\n",
      "Jinja2==2.11.1\n",
      "joblib==0.14.1\n",
      "json5==0.9.1\n",
      "jsonschema==3.2.0\n",
      "jupyter==1.0.0\n",
      "jupyter-client==5.3.4\n",
      "jupyter-console==6.1.0\n",
      "jupyter-core==4.6.1\n",
      "jupyterlab==1.2.6\n",
      "jupyterlab-server==1.0.6\n",
      "keyring==21.1.0\n",
      "kiwisolver==1.1.0\n",
      "lazy-object-proxy==1.4.3\n",
      "legacy-api-wrap==1.2\n",
      "libarchive-c==2.8\n",
      "lief==0.9.0\n",
      "llvmlite==0.35.0\n",
      "locket==0.2.0\n",
      "loompy==3.0.6\n",
      "lxml==4.5.0\n",
      "MarkupSafe==1.1.1\n",
      "matplotlib==3.1.3\n",
      "mccabe==0.6.1\n",
      "mistune==0.8.4\n",
      "mkl-fft==1.0.15\n",
      "mkl-random==1.1.0\n",
      "mkl-service==2.3.0\n",
      "mock==4.0.1\n",
      "more-itertools==8.2.0\n",
      "mpmath==1.1.0\n",
      "msgpack==0.6.1\n",
      "multipledispatch==0.6.0\n",
      "natsort==7.1.1\n",
      "navigator-updater==0.2.1\n",
      "nbconvert==5.6.1\n",
      "nbformat==5.0.4\n",
      "networkx==2.4\n",
      "nltk==3.4.5\n",
      "nose==1.3.7\n",
      "notebook==6.0.3\n",
      "numba==0.52.0\n",
      "numexpr==2.7.1\n",
      "numpy==1.18.1\n",
      "numpy-groupies==0.9.13\n",
      "numpydoc==0.9.2\n",
      "olefile==0.46\n",
      "openpyxl==3.0.3\n",
      "packaging==20.1\n",
      "pandas==1.0.1\n",
      "pandocfilters==1.4.2\n",
      "parso==0.5.2\n",
      "partd==1.1.0\n",
      "path==13.1.0\n",
      "pathlib2==2.3.5\n",
      "pathtools==0.1.2\n",
      "patsy==0.5.1\n",
      "pep8==1.7.1\n",
      "pexpect==4.8.0\n",
      "pickleshare==0.7.5\n",
      "Pillow==7.0.0\n",
      "pkginfo==1.5.0.1\n",
      "pluggy==0.13.1\n",
      "ply==3.11\n",
      "prometheus-client==0.7.1\n",
      "prompt-toolkit==3.0.3\n",
      "psutil==5.6.7\n",
      "ptyprocess==0.6.0\n",
      "py==1.8.1\n",
      "pycodestyle==2.5.0\n",
      "pycosat==0.6.3\n",
      "pycparser==2.19\n",
      "pycrypto==2.6.1\n",
      "pycurl==7.43.0.5\n",
      "pydocstyle==4.0.1\n",
      "pyflakes==2.1.1\n",
      "Pygments==2.5.2\n",
      "pylint==2.4.4\n",
      "pynndescent==0.5.1\n",
      "pyodbc===4.0.0-unsupported\n",
      "pyOpenSSL==19.1.0\n",
      "pyparsing==2.4.6\n",
      "pyrsistent==0.15.7\n",
      "PySocks==1.7.1\n",
      "pytest==5.3.5\n",
      "pytest-arraydiff==0.3\n",
      "pytest-astropy==0.8.0\n",
      "pytest-astropy-header==0.1.2\n",
      "pytest-doctestplus==0.5.0\n",
      "pytest-openfiles==0.4.0\n",
      "pytest-remotedata==0.3.2\n",
      "python-dateutil==2.8.1\n",
      "python-jsonrpc-server==0.3.4\n",
      "python-language-server==0.31.7\n",
      "pytz==2019.3\n",
      "PyWavelets==1.1.1\n",
      "pyxdg==0.26\n",
      "PyYAML==5.3\n",
      "pyzmq==18.1.1\n",
      "QDarkStyle==2.8\n",
      "QtAwesome==0.6.1\n",
      "qtconsole==4.6.0\n",
      "QtPy==1.9.0\n",
      "requests==2.22.0\n",
      "rope==0.16.0\n",
      "Rtree==0.9.3\n",
      "ruamel-yaml==0.15.87\n",
      "scanpy==1.6.1\n",
      "scikit-image==0.16.2\n",
      "scikit-learn==0.22.1\n",
      "scikit-learn-extra==0.1.0b2\n",
      "scipy==1.4.1\n",
      "scvelo==0.2.2\n",
      "seaborn==0.10.0\n",
      "SecretStorage==3.1.2\n",
      "Send2Trash==1.5.0\n",
      "setuptools-scm==5.0.1\n",
      "simplegeneric==0.8.1\n",
      "sinfo==0.3.1\n",
      "singledispatch==3.4.0.3\n",
      "six==1.14.0\n",
      "snowballstemmer==2.0.0\n",
      "sortedcollections==1.1.2\n",
      "sortedcontainers==2.1.0\n",
      "soupsieve==1.9.5\n",
      "Sphinx==2.4.0\n",
      "sphinxcontrib-applehelp==1.0.1\n",
      "sphinxcontrib-devhelp==1.0.1\n",
      "sphinxcontrib-htmlhelp==1.0.2\n",
      "sphinxcontrib-jsmath==1.0.1\n",
      "sphinxcontrib-qthelp==1.0.2\n",
      "sphinxcontrib-serializinghtml==1.1.3\n",
      "sphinxcontrib-websupport==1.2.0\n",
      "spyder==4.0.1\n",
      "spyder-kernels==1.8.1\n",
      "SQLAlchemy==1.3.13\n",
      "statsmodels==0.11.0\n",
      "stdlib-list==0.8.0\n",
      "sympy==1.5.1\n",
      "tables==3.6.1\n",
      "tblib==1.6.0\n",
      "terminado==0.8.3\n",
      "testpath==0.4.4\n",
      "toolz==0.10.0\n",
      "tornado==6.0.3\n",
      "tqdm==4.42.1\n",
      "traitlets==4.3.3\n",
      "ujson==1.35\n",
      "umap-learn==0.4.6\n",
      "unicodecsv==0.14.1\n",
      "urllib3==1.25.8\n",
      "watchdog==0.10.2\n",
      "wcwidth==0.1.8\n",
      "webencodings==0.5.1\n",
      "Werkzeug==1.0.0\n",
      "widgetsnbextension==3.5.1\n",
      "wrapt==1.11.2\n",
      "wurlitzer==2.0.0\n",
      "xlrd==1.2.0\n",
      "XlsxWriter==1.2.7\n",
      "xlwt==1.3.0\n",
      "xmltodict==0.12.0\n",
      "yapf==0.28.0\n",
      "zict==1.0.0\n",
      "zipp==2.2.0\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip freeze"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "... storing 'orig.ident' as categorical\n",
      "... storing 'Barcode' as categorical\n",
      "... storing 'Sample' as categorical\n",
      "... storing 'Sample_Origin' as categorical\n",
      "... storing 'Cell_type' as categorical\n",
      "... storing 'Cell_type.refined' as categorical\n",
      "... storing 'Cell_subtype' as categorical\n",
      "... storing 'No' as categorical\n",
      "... storing 'Patient.id' as categorical\n",
      "... storing 'Samples' as categorical\n",
      "... storing 'Tissue.origins' as categorical\n",
      "... storing 'Histology' as categorical\n",
      "... storing 'Sex' as categorical\n",
      "... storing 'Smoking' as categorical\n",
      "... storing 'Pathology' as categorical\n",
      "... storing 'EGFR' as categorical\n",
      "... storing 'Stages' as categorical\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sc.pl.umap(mapped_kim_data_imm, color='cell_type_imm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sc.pl.umap(mapped_kim_data_str, color='cell_type_str')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}