Cattle_data_exploration.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Installation\n",
    "```\n",
    "virtualenv -p python3 venv-cattle \n",
    "source venv-cattle/bin/activate  \n",
    "pip install ipykernel  \n",
    "python -m ipykernel install --user --name=opentree  \n",
    "pip install jupyter\n",
    "pip install numpy\n",
    "pip install pandas\n",
    "pip install rpy2\n",
    "jupyter notebook\n",
    "```\n",
    "\n",
    "*Need to install vcfR and adegent in R*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext rpy2.ipython"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "R[write to console]: \n",
      "   *****       ***   vcfR   ***       *****\n",
      "   This is vcfR 1.12.0 \n",
      "     browseVignettes('vcfR') # Documentation\n",
      "     citation('vcfR') # Citation\n",
      "   *****       *****      *****       *****\n",
      "\n",
      "\n",
      "R[write to console]: Loading required package: ade4\n",
      "\n",
      "R[write to console]: Registered S3 method overwritten by 'spdep':\n",
      "  method   from\n",
      "  plot.mst ape \n",
      "\n",
      "R[write to console]: \n",
      "   /// adegenet 2.1.3 is loaded ////////////\n",
      "\n",
      "   > overview: '?adegenet'\n",
      "   > tutorials/doc/questions: 'adegenetWeb()' \n",
      "   > bug reports/feature requests: adegenetIssues()\n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "setwd(\"~/Desktop/Lab/Joseline\")\n",
    "inputvcf = \"ChrALL.vcf\"\n",
    "inputnames = \"SummerGenomics/samplenames.csv\"\n",
    "##input names file generated by running\n",
    "# python vcf_manip/get_labels_pops.py -m metadata/label_match.csv -i samplenames.txt -o samplenames.csv\n",
    "\n",
    "library(vcfR)\n",
    "library(adegenet)\n",
    "\n",
    "label_map <- read.csv(inputnames)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                          filename ind_name      pop\n",
      "1     3592092.sorted.dedup.q20.bam      OG2   ogaden\n",
      "2     3693376.sorted.dedup.q20.bam      ND1    ndama\n",
      "3     3592093.sorted.dedup.q20.bam      OG4   ogaden\n",
      "4     3656921.sorted.dedup.q20.bam      AK2   ankole\n",
      "5  SRR6936540.sorted.dedup.q20.bam     IND1 indicine\n",
      "6     3491019.sorted.dedup.q20.bam      OG5   ogaden\n",
      "7     3546727.sorted.dedup.q20.bam     BOR3    boran\n",
      "8     3656922.sorted.dedup.q20.bam      AK4   ankole\n",
      "9     3693379.sorted.dedup.q20.bam      ND3    ndama\n",
      "10    3546729.sorted.dedup.q20.bam     BOR6    boran\n",
      "11    3693229.sorted.dedup.q20.bam     KEN6   kenana\n",
      "12    3546787.sorted.dedup.q20.bam     BOR8    boran\n",
      "13    3694478.sorted.dedup.q20.bam      ND7    ndama\n",
      "14    3694657.sorted.dedup.q20.bam     KEN8   kenana\n",
      "15    3592091.sorted.dedup.q20.bam      OG7   ogaden\n"
     ]
    }
   ],
   "source": [
    "%%R \n",
    "label_map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Scanning file to determine attributes.\n",
      "File attributes:\n",
      "  meta lines: 29\n",
      "  header_line: 30\n",
      "  variant count: 1177311\n",
      "  column count: 24\n",
      "Meta line 29 read in.\n",
      "All meta lines processed.\n",
      "gt matrix initialized.\n",
      "Character matrix gt created.\n",
      "  Character matrix gt rows: 1177311\n",
      "  Character matrix gt cols: 24\n",
      "  skip: 0\n",
      "  nrows: 1177311\n",
      "  row_num: 0\n",
      "Processed variant: 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      "All variants processed\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "\n",
    "\n",
    "vcf <- read.vcfR(inputvcf)\n",
    "mybov <- vcfR2genind(vcf)\n",
    "\n",
    "indNames(mybov)<-label_map$ind_name\n",
    "pop(mybov)<-label_map$pop\n",
    "\n",
    "\n",
    "x.cows <- tab(mybov, freq=TRUE, NA.method=\"mean\")\n",
    "pca.cows <- dudi.pca(df = x.cows, center = TRUE, scale = FALSE, nf = 3, scannf = FALSE)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "s.label(pca.cows$li)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "cattle",
   "language": "python",
   "name": "cattle"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}