Commit 59cb5bc2 authored by Geoff Stanley's avatar Geoff Stanley
Browse files

Initial commit

parent 2c3e073d
*.tab
*.csv
# Jupyter Notebook
.ipynb_checkpoints
{
"cells": [
{
"cell_type": "code",
"execution_count": 6,
"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>chr</th>\n",
" <th>b1</th>\n",
" <th>b2</th>\n",
" <th>id</th>\n",
" <th>nCounts.SS</th>\n",
" <th>nCells.SS</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>chr2</td>\n",
" <td>9952946</td>\n",
" <td>10042426</td>\n",
" <td>chr2_9952946_10042426</td>\n",
" <td>78213</td>\n",
" <td>4373</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>chr2</td>\n",
" <td>102813395</td>\n",
" <td>102855920</td>\n",
" <td>chr2_102813395_102855920</td>\n",
" <td>1306</td>\n",
" <td>122</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>chr2</td>\n",
" <td>102814338</td>\n",
" <td>102822207</td>\n",
" <td>chr2_102814338_102822207</td>\n",
" <td>91590</td>\n",
" <td>5922</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>chr2</td>\n",
" <td>102822287</td>\n",
" <td>102824260</td>\n",
" <td>chr2_102822287_102824260</td>\n",
" <td>111946</td>\n",
" <td>5913</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>chr2</td>\n",
" <td>102824333</td>\n",
" <td>102828541</td>\n",
" <td>chr2_102824333_102828541</td>\n",
" <td>103261</td>\n",
" <td>5757</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" chr b1 b2 id nCounts.SS nCells.SS\n",
"0 chr2 9952946 10042426 chr2_9952946_10042426 78213 4373\n",
"1 chr2 102813395 102855920 chr2_102813395_102855920 1306 122\n",
"2 chr2 102814338 102822207 chr2_102814338_102822207 91590 5922\n",
"3 chr2 102822287 102824260 chr2_102822287_102824260 111946 5913\n",
"4 chr2 102824333 102828541 chr2_102824333_102828541 103261 5757"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import scanpy.api as sc\n",
"sc.settings.set_figure_params(dpi=80)\n",
"\n",
"ss_metadata=pd.read_table(\"../data/cd44_spliceSite_summary.tsv\")\n",
"ss_metadata.head()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Index(['chr2_102813395_102855920', 'chr2_102814338_102822207',\n",
" 'chr2_102822287_102824260', 'chr2_102824333_102828541',\n",
" 'chr2_102828611_102831329', 'chr2_102828611_102853014',\n",
" 'chr2_102831537_102832482', 'chr2_102831537_102853014',\n",
" 'chr2_102832573_102834233', 'chr2_102832573_102853014',\n",
" 'chr2_102834336_102837812', 'chr2_102834336_102853014',\n",
" 'chr2_102837939_102839357', 'chr2_102837939_102842260',\n",
" 'chr2_102837939_102853014', 'chr2_102839478_102842260',\n",
" 'chr2_102839478_102842835', 'chr2_102839478_102853014',\n",
" 'chr2_102842378_102842835', 'chr2_102842950_102845284',\n",
" 'chr2_102842950_102853014', 'chr2_102845411_102846402',\n",
" 'chr2_102845411_102853014', 'chr2_102846520_102848656',\n",
" 'chr2_102846520_102853014', 'chr2_102848783_102853014',\n",
" 'chr2_102853237_102855898', 'chr2_102855968_102861559',\n",
" 'chr2_102861697_102865280', 'chr2_102865447_102901267',\n",
" 'chr2_9952946_10042426'],\n",
" dtype='object', name='index')\n",
"Index(['Bladder_bladder cell', 'Bladder_bladder urothelial cell',\n",
" 'Brain_Myeloid_macrophage', 'Brain_Myeloid_microglial cell',\n",
" 'Brain_Non-Myeloid_astrocyte', 'Brain_Non-Myeloid_Bergmann glial cell',\n",
" 'Brain_Non-Myeloid_brain pericyte',\n",
" 'Brain_Non-Myeloid_endothelial cell', 'Brain_Non-Myeloid_neuron',\n",
" 'Brain_Non-Myeloid_oligodendrocyte',\n",
" ...\n",
" 'Spleen_T cell', 'Thymus_DN1 thymic pro-T cell',\n",
" 'Thymus_immature T cell', 'Thymus_leukocyte',\n",
" 'Tongue_basal cell of epidermis', 'Tongue_keratinocyte',\n",
" 'Trachea_blood cell', 'Trachea_endothelial cell',\n",
" 'Trachea_epithelial cell', 'Trachea_mesenchymal cell'],\n",
" dtype='object', name='index', length=115)\n"
]
}
],
"source": [
"path = '../data/'\n",
"adata = sc.read(path + 'cd44_celltype_fracCells.csv', cache=True).T # transpose the data\n",
"print(adata.var_names)\n",
"print(adata.obs_names)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
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"pygments_lexer": "ipython3",
"version": "3.6.5"
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"nbformat": 4,
"nbformat_minor": 2
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