examples/PBMC_multiome/make_anndata.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
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   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import h5py\n",
    "import scipy\n",
    "import scanpy as sc\n",
    "import anndata\n",
    "from scbasset.utils import *\n",
    "\n",
    "# plotting functions\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import os"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### read example from 10x multiome output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_path = '../../data/multiome_pbmc/'\n",
    "\n",
    "h5_file = data_path + 'pbmc_granulocyte_sorted_3k_filtered_feature_bc_matrix.h5'\n",
    "bed_file = data_path + 'pbmc_granulocyte_sorted_3k_atac_peaks.bed'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n"
     ]
    }
   ],
   "source": [
    "peak = pd.read_csv(bed_file, sep='\\t', names=['chr','start','end'])\n",
    "ad = sc.read_10x_h5(h5_file, gex_only=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### filtering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Trying to set attribute `.var` of view, copying.\n",
      "Trying to set attribute `.obs` of view, copying.\n",
      "Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n",
      "Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n",
      "Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n",
      "Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n",
      "Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n",
      "Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n"
     ]
    }
   ],
   "source": [
    "ad_rna = ad[:, ad.var['feature_types']=='Gene Expression']\n",
    "ad_atac = ad[:, ad.var['feature_types']=='Peaks']\n",
    "ad_atac.var['chr'] = peak['chr'].values\n",
    "ad_atac.var['start'] = peak['start'].values\n",
    "ad_atac.var['end'] = peak['end'].values\n",
    "\n",
    "# basic stats\n",
    "sc.pp.filter_cells(ad_rna, min_genes=0)\n",
    "sc.pp.filter_genes(ad_rna, min_cells=0)\n",
    "sc.pp.filter_cells(ad_atac, min_genes=0)\n",
    "sc.pp.filter_genes(ad_atac, min_cells=0)\n",
    "\n",
    "# a gene need to be expressed in 5% cells\n",
    "# a peak need to be accessible in 5% cells\n",
    "thres = int(ad.shape[0]*0.05)\n",
    "ad_rna = ad_rna[:, ad_rna.var['n_cells']>thres]\n",
    "ad_atac = ad_atac[:, ad_atac.var['n_cells']>thres]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### save h5ad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/yuanh/.local/lib/python3.7/site-packages/anndata/_core/anndata.py:1228: FutureWarning: The `inplace` parameter in pandas.Categorical.reorder_categories is deprecated and will be removed in a future version. Reordering categories will always return a new Categorical object.\n",
      "  c.reorder_categories(natsorted(c.categories), inplace=True)\n",
      "/home/yuanh/.local/lib/python3.7/site-packages/anndata/_core/anndata.py:1237: ImplicitModificationWarning: Initializing view as actual.\n",
      "  \"Initializing view as actual.\", ImplicitModificationWarning\n",
      "Trying to set attribute `.var` of view, copying.\n",
      "... storing 'feature_types' as categorical\n",
      "/home/yuanh/.local/lib/python3.7/site-packages/anndata/_core/anndata.py:1228: FutureWarning: The `inplace` parameter in pandas.Categorical.reorder_categories is deprecated and will be removed in a future version. Reordering categories will always return a new Categorical object.\n",
      "  c.reorder_categories(natsorted(c.categories), inplace=True)\n",
      "Trying to set attribute `.var` of view, copying.\n",
      "... storing 'genome' as categorical\n",
      "/home/yuanh/.local/lib/python3.7/site-packages/anndata/_core/anndata.py:1228: FutureWarning: The `inplace` parameter in pandas.Categorical.reorder_categories is deprecated and will be removed in a future version. Reordering categories will always return a new Categorical object.\n",
      "  c.reorder_categories(natsorted(c.categories), inplace=True)\n",
      "Trying to set attribute `.var` of view, copying.\n",
      "... storing 'chr' as categorical\n"
     ]
    }
   ],
   "source": [
    "chrs = ['chr'+str(i) for i in range(1,23)] + ['chrX', 'chrY']\n",
    "ad_atac = ad_atac[:, ad_atac.var['chr'].isin(chrs)]\n",
    "ad_atac.write('atac_ad.h5ad')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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