MendelGwas/GWASNotebook.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MendelGWAS.jl"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook is designed to be a guide on how to use the package MendelGWAS in Open Mendel to perform a Genome Wide Association Study (GWAS). It will cover performing a GWAS on both qualitative and quantitative tratits (linear and logistic regression). "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data we will be using is from the Mendel version 16 sample files. The data is described in examples under Option 24 in the Mendel Version 16 Manual [Section 24.4,  page 250](http://software.genetics.ucla.edu/download?file=202). It consists of simulated data where the traits (binary and quantitative) of interest have two contributing SNPs and an interaction between them."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "MendelGWAS requires the following packages to be installed in the following order: SnpArrays.jl, MendelSearch.jl, MendelBase.jl, MendelPlots.jl. If not already done, it can be done through the following commands:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m registry at `~/.julia/registries/General`\n",
      "\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m git-repo `https://github.com/JuliaRegistries/General.git`\n",
      "\u001b[?25l\u001b[2K\u001b[?25h\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m git-repo `https://github.com/OpenMendel/SnpArrays.jl.git`\n",
      "\u001b[?25l\u001b[2K\u001b[?25h\u001b[32m\u001b[1m Resolving\u001b[22m\u001b[39m package versions...\n",
      "\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m `~/.julia/environments/v1.1/Project.toml`\n",
      "\u001b[90m [no changes]\u001b[39m\n",
      "\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m `~/.julia/environments/v1.1/Manifest.toml`\n",
      "\u001b[90m [no changes]\u001b[39m\n",
      "\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m git-repo `https://github.com/OpenMendel/MendelSearch.jl.git`\n",
      "\u001b[?25l\u001b[2K\u001b[?25h\u001b[32m\u001b[1m Resolving\u001b[22m\u001b[39m package versions...\n",
      "\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m `~/.julia/environments/v1.1/Project.toml`\n",
      "\u001b[90m [no changes]\u001b[39m\n",
      "\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m `~/.julia/environments/v1.1/Manifest.toml`\n",
      "\u001b[90m [no changes]\u001b[39m\n",
      "\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m git-repo `https://github.com/OpenMendel/MendelBase.jl.git`\n",
      "\u001b[?25l\u001b[2K\u001b[?25h\u001b[32m\u001b[1m Resolving\u001b[22m\u001b[39m package versions...\n",
      "\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m `~/.julia/environments/v1.1/Project.toml`\n",
      "\u001b[90m [no changes]\u001b[39m\n",
      "\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m `~/.julia/environments/v1.1/Manifest.toml`\n",
      "\u001b[90m [no changes]\u001b[39m\n"
     ]
    }
   ],
   "source": [
    "using Pkg\n",
    "Pkg.add(PackageSpec(url=\"https://github.com/OpenMendel/SnpArrays.jl.git\"))\n",
    "Pkg.add(PackageSpec(url=\"https://github.com/OpenMendel/MendelSearch.jl.git\"))\n",
    "Pkg.add(PackageSpec(url=\"https://github.com/OpenMendel/MendelBase.jl.git\"))\n",
    "Pkg.add(PackageSpec(url=\"https://github.com/OpenMendel/MendelPlots.jl.git\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Add MendelGWAS.jl to your computer if it's not already installed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m git-repo `https://github.com/OpenMendel/MendelPlots.jl.git`\n",
      "\u001b[?25l\u001b[2K\u001b[?25h\u001b[32m\u001b[1m Resolving\u001b[22m\u001b[39m package versions...\n",
      "\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m `~/.julia/environments/v1.1/Project.toml`\n",
      "\u001b[90m [no changes]\u001b[39m\n",
      "\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m `~/.julia/environments/v1.1/Manifest.toml`\n",
      "\u001b[90m [no changes]\u001b[39m\n"
     ]
    }
   ],
   "source": [
    "Pkg.add(PackageSpec(url=\"https://github.com/OpenMendel/MendelGWAS.jl.git\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For reproducability information, run versioninfo()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Julia Version 1.1.0\n",
      "Commit 80516ca202 (2019-01-21 21:24 UTC)\n",
      "Platform Info:\n",
      "  OS: macOS (x86_64-apple-darwin14.5.0)\n",
      "  CPU: Intel(R) Core(TM) i7-6567U CPU @ 3.30GHz\n",
      "  WORD_SIZE: 64\n",
      "  LIBM: libopenlibm\n",
      "  LLVM: libLLVM-6.0.1 (ORCJIT, skylake)\n",
      "Environment:\n",
      "  JULIA_NUM_THREADS = 8\n"
     ]
    }
   ],
   "source": [
    "versioninfo()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "MendelGWAS requires a `.txt` file as input with certain fields in order to run the analysis with additional optional fields for further customization and additional analyses."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Required Arguments:\n",
    "\n",
    "`pedigree_file` is the file with your covariates. Note: The covariate file must have a row of 1s labeled Person. \n",
    "\n",
    "`snpdefinition_file` is the file where your SNPs are defined (snp, chromosome, basepair).\n",
    "\n",
    "`snpdata_file` is the file with your SNP data.\n",
    "\n",
    "or alternatively instead of the three above, you can use:\n",
    "\n",
    "`plink_input_basename` which is the basename of the plink file.\n",
    "\n",
    "`output_file` is the file that is outputted with the results.\n",
    "\n",
    "`regression` is the choice of regression.\n",
    "\n",
    "`regression_formula` is the formula for the regression written in R-like syntax. The left hand side of formula (to the left of `~`) is the trait variable. \n",
    "\n",
    "$\\hspace{5mm}$\n",
    "\n",
    "## Optional arguments:\n",
    "\n",
    "`manhattan_plot_file` is the name of the file for the manhattan plot generated from the analysis. A Manhattan Plot will only be generated if this argument is in the `.txt` file. File name must end in either .png, .svg, or .pdf. \n",
    "\n",
    "\n",
    "`qq_plot_file` is the name of the .png file for the QQ plot generated from the analysis result. A QQ will only be generated if this argument is in the `.txt` file. File name must end in either .png, .svg, or .pdf. \n",
    "\n",
    "`output_table` is the name of the csv file that contains all SNP information and their pvalues from the GWAS results. \n",
    "\n",
    "`lrt_threshold` default is set to 5e-8.\n",
    "\n",
    "`maf_threshold` default is set to 0.01.\n",
    "\n",
    "`min_success_rate_per_sample` default is set to 0.98.\n",
    "\n",
    "`min_success_rate_per_snp`  default is set to 0.98.\n",
    "\n",
    "`pcs` is the number of Principal Components to calculate and include in the model, default is set to 0."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ensure your directory is set to the correct location containing all relevant files using:\n",
    "\n",
    "`;cd path`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$\\bf{Qualitative}$ $\\bf{GWAS}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will first demonstrate using MendelGWAS to perform an analysis with a dichotomous trait such as disease presence or absence. \n",
    "You will need to have a `.txt` file that has the required information as well as optional keywords. The example file we will use for the analysis is shown below. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "#\n",
      "# Input and Output files.\n",
      "#\n",
      "pedigree_file = gwasped.txt\n",
      "snpdefinition_file = gwassnpdef.txt\n",
      "snpdata_file = gwasdata.bed\n",
      "output_file = qualOutput.txt\n",
      "manhattan_plot_file = qualManhattanPlotOutput.png\n",
      "qq_plot_file = qualqq.png\n",
      "output_table = qualresults.csv\n",
      "#\n",
      "# Analysis parameters for GWAS option.\n",
      "#\n",
      "regression = logistic\n",
      "regression_formula = Case_Control ~ Sex + BMI\n"
     ]
    }
   ],
   "source": [
    ";cat qualControl.txt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To run the analysis, simply specify 'Using MendelGWAS' and then enter the commend GWAS(\"file.txt\")."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: Loading Cairo backend into Compose.jl\n",
      "└ @ Compose /Users/janets/.julia/packages/Compose/wlPCt/src/Compose.jl:164\n",
      "┌ Info: Loading DataFrames support into Gadfly.jl\n",
      "└ @ Gadfly /Users/janets/.julia/packages/Gadfly/09PWZ/src/mapping.jl:228\n",
      "┌ Info: Recompiling stale cache file /Users/janets/.julia/compiled/v1.1/MendelGWAS/y6a7g.ji for MendelGWAS [c1bad3ca-268b-5bf6-b82e-de8a361f94db]\n",
      "└ @ Base loading.jl:1184\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " \n",
      " \n",
      "     Welcome to OpenMendel's\n",
      "      GWAS analysis option\n",
      "        version 0.5.0\n",
      " \n",
      " \n",
      "Reading the data.\n",
      "\n",
      "The current working directory is \"/Users/janets/Documents/lap_top_janet/janet/genetics/review_August2018/revision/OpenMendelTutorials/MendelGwas\".\n",
      "\n",
      "Keywords modified by the user:\n",
      "\n",
      "  control_file = qualControl.txt\n",
      "  manhattan_plot_file = qualManhattanPlotOutput.png\n",
      "  output_file = qualOutput.txt\n",
      "  output_table = qualresults.csv\n",
      "  pedigree_file = gwasped.txt\n",
      "  qq_plot_file = qualqq.png\n",
      "  regression = logistic\n",
      "  regression_formula = Case_Control ~ Sex + BMI\n",
      "  snpdata_file = gwasdata.bed\n",
      "  snpdefinition_file = gwassnpdef.txt\n",
      " \n",
      " \n",
      "Analyzing the data.\n",
      "\n",
      " \n",
      "Plots being drawn using MendelPlots package.\n",
      " \n",
      "Manhattan plot of GWAS results is in file: qualManhattanPlotOutput.png\n",
      " \n",
      "QQ plot of GWAS results is in file: qualqq.png\n",
      " \n",
      " \n",
      "Mendel's analysis is finished.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "using MendelGWAS\n",
    "GWAS(\"qualControl.txt\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now to check on the results. They are stored in the designated output file in the same directory. The file contains the base model information as well as significant SNPs and relevant information for them. In the Analysis, there were 2 SNPs detected to be potentially significant (p-value < 0.05/number of snps), so only their output is included in the output file. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " \n",
      "Summary for Base Model with Formula: Case_Control ~ Sex + BMI\n",
      "Regression model: logistic\n",
      "Link function: canonical\n",
      "Base components' effect estimates: \n",
      "   (Intercept) : -0.699975\n",
      "   Sex : 0.0132831\n",
      "   BMI : -0.00875774\n",
      "Base model loglikelihood: -1315.0784\n",
      " \n",
      " \n",
      "\n",
      "Summary for SNP rs1935681\n",
      " on chromosome 6 at basepair 112651205\n",
      "SNP p-value: 1.515e-9\n",
      "Minor allele frequency: 0.2523\n",
      "Hardy-Weinberg p-value: 0.3666\n",
      "SNP effect estimate: 0.4831\n",
      "SNP model loglikelihood: -1296.8209\n",
      " \n",
      "\n",
      "Summary for SNP rs2256412\n",
      " on chromosome 12 at basepair 41913108\n",
      "SNP p-value: 6.68e-21\n",
      "Minor allele frequency: 0.4741\n",
      "Hardy-Weinberg p-value: 0.1844\n",
      "SNP effect estimate: 0.6371\n",
      "SNP model loglikelihood: -1271.0984\n",
      " \n",
      " \n",
      " \n",
      "        P-value   Number of Passing\n",
      "FDR    Threshold     Predictors \n",
      "\n",
      "0.01    0.00000           2\n",
      "0.05    0.00000           2\n",
      "0.10    0.00000           2\n",
      "0.20    0.00000           2\n",
      "0.30    0.00000           2\n",
      "0.40    0.00000           2\n",
      "0.50    0.00000           2\n",
      "0.60    0.00044           8\n",
      "0.70    0.00108          16\n",
      "0.80    0.00540          68\n",
      "0.90    0.02661         297\n",
      " \n"
     ]
    }
   ],
   "source": [
    ";cat qualOutput.txt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To view the output file that was generated: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SNP,Chromosome,BasePair,Pvalue,NegLog10Pvalue\n",
      "rs3934834,1,1005805,0.7563277049400371,0.12128999072883717\n",
      "rs6603793,1,1505254,0.8685887471231099,0.061185801377192435\n",
      "rs2843153,1,2245220,0.2878278863416084,0.5408671315336122\n",
      "rs7535528,1,2444413,0.32797229375701864,0.48416284280256167\n",
      "rs12046158,1,2891712,0.18377742614762207,0.7357078351784448\n",
      "rs2817134,1,3098714,0.7345730341301177,0.13396501846750467\n",
      "rs4494089,1,3254355,0.6061077172766064,0.21745018629306131\n",
      "rs4648505,1,3405295,0.4027894996634027,0.3949218596121692\n",
      "rs1181883,1,3677932,0.7097702689879541,0.14888219642953585\n"
     ]
    }
   ],
   "source": [
    ";head qualresults.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For benchmarking purposes, we created a control file that omits the creation of the plots. If you run this version (qualControl2.txt) you can get an idea of how fast you can run a GWAS in Open Mendel on your particular platform."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " \n",
      " \n",
      "     Welcome to OpenMendel's\n",
      "      GWAS analysis option\n",
      "        version 0.5.0\n",
      " \n",
      " \n",
      "Reading the data.\n",
      "\n",
      "The current working directory is \"/Users/janets/Documents/lap_top_janet/janet/genetics/review_August2018/revision/OpenMendelTutorials/MendelGwas\".\n",
      "\n",
      "Keywords modified by the user:\n",
      "\n",
      "  control_file = qualControl2.txt\n",
      "  output_file = qualOutput.txt\n",
      "  output_table = qualresults.csv\n",
      "  pedigree_file = gwasped.txt\n",
      "  regression = logistic\n",
      "  regression_formula = Case_Control ~ Sex + BMI\n",
      "  snpdata_file = gwasdata.bed\n",
      "  snpdefinition_file = gwassnpdef.txt\n",
      " \n",
      " \n",
      "Analyzing the data.\n",
      "\n",
      " \n",
      " \n",
      "Mendel's analysis is finished.\n",
      "\n",
      " \n",
      " \n",
      "     Welcome to OpenMendel's\n",
      "      GWAS analysis option\n",
      "        version 0.5.0\n",
      " \n",
      " \n",
      "Reading the data.\n",
      "\n",
      "The current working directory is \"/Users/janets/Documents/lap_top_janet/janet/genetics/review_August2018/revision/OpenMendelTutorials/MendelGwas\".\n",
      "\n",
      "Keywords modified by the user:\n",
      "\n",
      "  control_file = qualControl2.txt\n",
      "  output_file = qualOutput.txt\n",
      "  output_table = qualresults.csv\n",
      "  pedigree_file = gwasped.txt\n",
      "  regression = logistic\n",
      "  regression_formula = Case_Control ~ Sex + BMI\n",
      "  snpdata_file = gwasdata.bed\n",
      "  snpdefinition_file = gwassnpdef.txt\n",
      " \n",
      " \n",
      "Analyzing the data.\n",
      "\n",
      " \n",
      " \n",
      "Mendel's analysis is finished.\n",
      "\n",
      " \n",
      " \n",
      "     Welcome to OpenMendel's\n",
      "      GWAS analysis option\n",
      "        version 0.5.0\n",
      " \n",
      " \n",
      "Reading the data.\n",
      "\n",
      "The current working directory is \"/Users/janets/Documents/lap_top_janet/janet/genetics/review_August2018/revision/OpenMendelTutorials/MendelGwas\".\n",
      "\n",
      "Keywords modified by the user:\n",
      "\n",
      "  control_file = qualControl2.txt\n",
      "  output_file = qualOutput.txt\n",
      "  output_table = qualresults.csv\n",
      "  pedigree_file = gwasped.txt\n",
      "  regression = logistic\n",
      "  regression_formula = Case_Control ~ Sex + BMI\n",
      "  snpdata_file = gwasdata.bed\n",
      "  snpdefinition_file = gwassnpdef.txt\n",
      " \n",
      " \n",
      "Analyzing the data.\n",
      "\n",
      " \n",
      " \n",
      "Mendel's analysis is finished.\n",
      "\n",
      " \n",
      " \n",
      "     Welcome to OpenMendel's\n",
      "      GWAS analysis option\n",
      "        version 0.5.0\n",
      " \n",
      " \n",
      "Reading the data.\n",
      "\n",
      "The current working directory is \"/Users/janets/Documents/lap_top_janet/janet/genetics/review_August2018/revision/OpenMendelTutorials/MendelGwas\".\n",
      "\n",
      "Keywords modified by the user:\n",
      "\n",
      "  control_file = qualControl2.txt\n",
      "  output_file = qualOutput.txt\n",
      "  output_table = qualresults.csv\n",
      "  pedigree_file = gwasped.txt\n",
      "  regression = logistic\n",
      "  regression_formula = Case_Control ~ Sex + BMI\n",
      "  snpdata_file = gwasdata.bed\n",
      "  snpdefinition_file = gwassnpdef.txt\n",
      " \n",
      " \n",
      "Analyzing the data.\n",
      "\n",
      " \n",
      " \n",
      "Mendel's analysis is finished.\n",
      "\n",
      " \n",
      " \n",
      "     Welcome to OpenMendel's\n",
      "      GWAS analysis option\n",
      "        version 0.5.0\n",
      " \n",
      " \n",
      "Reading the data.\n",
      "\n",
      "The current working directory is \"/Users/janets/Documents/lap_top_janet/janet/genetics/review_August2018/revision/OpenMendelTutorials/MendelGwas\".\n",
      "\n",
      "Keywords modified by the user:\n",
      "\n",
      "  control_file = qualControl2.txt\n",
      "  output_file = qualOutput.txt\n",
      "  output_table = qualresults.csv\n",
      "  pedigree_file = gwasped.txt\n",
      "  regression = logistic\n",
      "  regression_formula = Case_Control ~ Sex + BMI\n",
      "  snpdata_file = gwasdata.bed\n",
      "  snpdefinition_file = gwassnpdef.txt\n",
      " \n",
      " \n",
      "Analyzing the data.\n",
      "\n",
      " \n",
      " \n",
      "Mendel's analysis is finished.\n",
      "\n",
      " \n",
      " \n",
      "     Welcome to OpenMendel's\n",
      "      GWAS analysis option\n",
      "        version 0.5.0\n",
      " \n",
      " \n",
      "Reading the data.\n",
      "\n",
      "The current working directory is \"/Users/janets/Documents/lap_top_janet/janet/genetics/review_August2018/revision/OpenMendelTutorials/MendelGwas\".\n",
      "\n",
      "Keywords modified by the user:\n",
      "\n",
      "  control_file = qualControl2.txt\n",
      "  output_file = qualOutput.txt\n",
      "  output_table = qualresults.csv\n",
      "  pedigree_file = gwasped.txt\n",
      "  regression = logistic\n",
      "  regression_formula = Case_Control ~ Sex + BMI\n",
      "  snpdata_file = gwasdata.bed\n",
      "  snpdefinition_file = gwassnpdef.txt\n",
      " \n",
      " \n",
      "Analyzing the data.\n",
      "\n",
      " \n",
      " \n",
      "Mendel's analysis is finished.\n",
      "\n",
      " \n",
      " \n",
      "     Welcome to OpenMendel's\n",
      "      GWAS analysis option\n",
      "        version 0.5.0\n",
      " \n",
      " \n",
      "Reading the data.\n",
      "\n",
      "The current working directory is \"/Users/janets/Documents/lap_top_janet/janet/genetics/review_August2018/revision/OpenMendelTutorials/MendelGwas\".\n",
      "\n",
      "Keywords modified by the user:\n",
      "\n",
      "  control_file = qualControl2.txt\n",
      "  output_file = qualOutput.txt\n",
      "  output_table = qualresults.csv\n",
      "  pedigree_file = gwasped.txt\n",
      "  regression = logistic\n",
      "  regression_formula = Case_Control ~ Sex + BMI\n",
      "  snpdata_file = gwasdata.bed\n",
      "  snpdefinition_file = gwassnpdef.txt\n",
      " \n",
      " \n",
      "Analyzing the data.\n",
      "\n",
      " \n",
      " \n",
      "Mendel's analysis is finished.\n",
      "\n",
      " \n",
      " \n",
      "     Welcome to OpenMendel's\n",
      "      GWAS analysis option\n",
      "        version 0.5.0\n",
      " \n",
      " \n",
      "Reading the data.\n",
      "\n",
      "The current working directory is \"/Users/janets/Documents/lap_top_janet/janet/genetics/review_August2018/revision/OpenMendelTutorials/MendelGwas\".\n",
      "\n",
      "Keywords modified by the user:\n",
      "\n",
      "  control_file = qualControl2.txt\n",
      "  output_file = qualOutput.txt\n",
      "  output_table = qualresults.csv\n",
      "  pedigree_file = gwasped.txt\n",
      "  regression = logistic\n",
      "  regression_formula = Case_Control ~ Sex + BMI\n",
      "  snpdata_file = gwasdata.bed\n",
      "  snpdefinition_file = gwassnpdef.txt\n",
      " \n",
      " \n",
      "Analyzing the data.\n",
      "\n",
      " \n",
      " \n",
      "Mendel's analysis is finished.\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "BenchmarkTools.Trial: \n",
       "  memory estimate:  1.53 GiB\n",
       "  allocs estimate:  1464448\n",
       "  --------------\n",
       "  minimum time:     1.901 s (18.96% GC)\n",
       "  median time:      1.991 s (18.79% GC)\n",
       "  mean time:        1.961 s (18.87% GC)\n",
       "  maximum time:     1.992 s (18.77% GC)\n",
       "  --------------\n",
       "  samples:          3\n",
       "  evals/sample:     1"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using BenchmarkTools\n",
    "@benchmark GWAS(\"qualControl2.txt\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A Manhattan Plot was generated from the analysis, this gives you a clear way to visualize where the significant hits are coming from and if any other SNPs were close to hitting the potentially significant boundary. \n",
    "\n",
    "The QQ plot was also generated, showing you the genomic inflation factor and the spread of the values. Because we don't expect the vast majority of the snps to be associated with the trait, most of the values of the QQ plot should fall close to their expected values under the null hypothesis of no association.  This is what we observe.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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02TWcoUF4VvradZ/9jz9MyvO6j6obZ7uOlStWPrHW9h91G1OSsfauvHL9xzf8oNu41pbW1iTvW/XcVWO7hne+dz9NVb9w+0NuX53kb+6T4wA8iwAAMNtsOQEAAMBAqrVxb/vA5Zdffnvt/AKvMb5nvDmdOYZ3Db8gyYKJo+XyvT8NWxu9aGdIkvxcx0itb1q/ef1b9/eSdl9jm1u/n1Lf12XII6aSb39qybW1kV/s8oL2PtZvXP+2pFzUPWfj+b2p7i4lee+S7Usf36mZYd/p129e/9qkdH1R2W7npElOP/D3uA/Mi2s4CM9KP2ue0DxmZPmp70wtb9zP0HYdL++Y7XradzUzLOoUr8mVY5tap++zAkdXF1918baxTa3TSvLOrgNLfUOz2ezJSkEAANBPNDQAAAAwLzRqXdcpVur+tguYxnklY9PJ2c1JJ510WDovmf6denA5d7q5y/jQu7uEH3Lsscf2ahXHry7Igl9uXdm6cSonDZfh/5VkZ+cRtfOS61P30fbSvHLtlrVd5vtxN2+/+S1Jbus4oJSf2V+OeXKP59Q8uoaD8Kz0m3L6iacf0VzW/LWR5c0NZTxfS8qrk3RvKCv5cOtjrf+czcJOe95pR5fkhM4l5Ou7F+5elUlsSzOR9tL8Tk2u6TLkf2Tb9P5fBwAA/Wxe/EUWAAAAdizY9ZGD9izameSgHwuW/ELzhOYjWle0vjnZfM1lzcOT/OqEwZrv3bz95k9Mt9ZOFu5c+JhaOq4F/pFWa/2Ee61Pxg/LD685JAfvysTbcpQHPOABi5PcMd38dxuvjay65MpLOr/07+CSjZfc1lze/HhJjp8oXpPDZljbPXbWmpe0Wq3xqZ64ZcuWPSuXN6+syaqJ4jV58P5yzIN7POfmyTUchGel92p50ciy5n6fkx9TcnBJHl6Th4/v2XNQmdp6OHeMp/2GKc85RbUxfna6fHisXfLWyy+//Pbp5m+1WrtWHr/yJbXd/kI6NXDUvCLJJdOdAwAA+pEVGgAAAJgXPvKRj9xRk00dwqW0y8iUEjZyUjp9EKBRP7xly5Y9U6tw/2qjPrpjLPX/zST35s2b70zy/Znk2L/yntaVrc9M9+xG6t93zFz33ywwOeXvWptbt0z79Fo/3jFzcvh+Tx/4ezz35sc1HIRnZVYsSsmJU/6V/FpNHpOJGtb2oyavvnTjpV/v/bfyI8cee+xwTV7eZcgPD9p9UMdVhCZr7Mqxq1PT8We8lPxCs9mcqBkHAAAGlhUaAAAAmDdKylhST54oVmtdmeRtk87VZbuJxnjvt5u4K2/jU+2hPX84UWy83e74In0ymsc2D05yxExy7E9plAtncn6tjS+ldFiNvfTmU+elPbMa26Xc3OXD4ft9kTzo97gfzIdrOAjPyvxQ393atGHtbM9yxCFHPLmOtx/UpY6LL77q4m09mayUVlKf2SF6UO7I05N8qidzAQBAH9DQAAAAwLyxY2jHlYvHD9qWZOm+sZI87ZQVpzxqMp/UPf3E048Y37Pn2R3CN48fUrbMsNQJrfvouuuTvHk2cmdxnpf97TM/AyX5+tiVY1fPJEet9dYuS8kvmknuu+24aedNX5hRhka+n067HUzi0+ODfI/7xaBfwwF5VuaB8ifrN7V+70DMVMc7NhjcFU95T6/mauxpbGgPj/9lOv2cDuXZ0dAAAMA8YssJAAAA5o0rrrhie2q5olN8qJaOqy7sbc/uPScnGZooVkoubbVa49Ms8YBrNptDzRXNFaWRi2Zznlry5ZknyfS3gphU+nxhpluFNMYb3+tVPb1yoO7xfHYgr+EgPCsD7sZS60vXb1p/QJoZkqSk/mKX8P9rbWr9e6/mWnfVum8l6dgQU2p9Qq/mAgCAfmCFBgAAAOabsSSnTRwqK5P8yf4SlNJ5u4lS6vrpFjabTjjhhCVL2kseWcfrMWWofXRqObqmHJ1t9dlJHjLb85ear800x9I7l27fvqQ3q7JPpJR67YxzLCg76oxaIqZvru/xfNAP13AQnpUBdX1NLsjSnLe+tWHHgZy4ljw9nXYAKflc7yfMN1Pysx2K6bL1BQAADB4NDQAAAMwrS3Ys+ej2Jdt+mOQBE4R/pvm85uNaH219pdP5Jx938pFJfrlD+Ds/9bQn/nOu3NCLUqeleVzz0aVRfiUlj0vaRyfl6CRHZzwPqWknjaTWe1Yi7/CGbRbUlNsP2GTTVGr/15j07z0eJP18DQfhWZllN8zo7JKdqbm1JreWlFuSfKaO14+3Ptb6z96UNw01R3YKtWu+2fP5Srm5489tiYYGAADmFQ0NAAAAzCtrt6zduXJ58+9rsmrCAUNZmeQPOp0/1Bg6JZ22aKxlw+joaLsXdU5Wc1nz8JSsKCm/mtRfTfLwH73ImngL9TlR29vnuoT9aZf8YK5rmMjA3OM+NlDXcACelVlT6vvWb9zw8rkuYxYs7RRolPqtXk9War2pdv6x1tAAAMC8oqEBAACAeaddMlZqh4aGZCRdGhpKIys7ffC11gO33cTo6Gjj2n+99pWl5K1JHtjvn8QvjRzQJd6no5H6w7muYW+Ddo/70SBew0F4Vuid2m70vKGhXXJLx36Gmgf2ej4AAJhLE3/iBAAAAAbYod899Kokt00UKzVPOP24U54wUezkZSc/LDW/1CHtja2Ptj7dqxq7OW3ZKT933Weu/ZdSckEyGC+nam3snusa9qefahzEe9xvBvUa9tPPIbOvDvd+hYYkQx0jJeOzMB8AAMwZDQ0AAADMOxd+/sLdJflwp/j4cFk50fGhMnRKOq1PX0srB+Dj3yuXnfqSdml8NsnTe5Tyq6Xmj0saj0ty/13qvo+4xzPnGjIwdvR+q5tSylFdwrf3ej4AAJhLtpwAAABgXmonYyWZeK/2WkaSvHmCyEinfCVlrEeldbRy2anPraW8N90+fTux8STfSvLfKfW/0851aTT+bdeCXV+4/PLL7325NbK82ctymQb3eOZcQwZJe3H7yKTHTQ21fVTH3rsOqxMBAMCg0tAAAADA/LQ0/5htuSXJ4RNEH9dc3vzZ1qbWF+850Dyh+YgynmdOlKok3xjbPPavs1VqkixbtmxRLeVvMrm/q/9Xarmilvpvw+Ptf/vOnd/7ypYtW/bMZn3MnHs8c64hg2aoPfTIJF/ubdbykx0j1QoNAADMLxoaAAAAmJdardb4yPJTL03Kb04UbyQrk9zb0JDxnJoOH3mttc76dhMPaCw9q9Y8Yj/Dvtho19ev++iGf5zteug993jmXEMGTU195Cyk7djQkEa5dRbmAwCAOdOY6wIAAABgtjQa6bZNxL7bS3TebqIOre9NRZ21azmtW7wmnxsuC35t3Uc3fCLTeEnbbDaHkiyabn3MnHs8c64hfeqOToFGe78NOFOy6rmrliZ5eJchX+wSAwCAgaOhAQAAgHnrp572xH9O8p2JYjV51Mrnrfz5JGme0DymJM+YaFxJvj720bHPzmKZaR7XfFBJfr5TvCbXZFeec8nGS6a9N/r4tvGHJRma7vnMjHs8c64hfavmax1jJY/u5VQ7h3c+P8nCLrV8ppfzAQDAXNPQAAAAwLw1OjraTmqrU7wO1ZVJ7tluopNZX50hC/K4dPk7eqn1g62Pt34wkymGMzwby54zWe7xzLmG9KnSyP/tFKvJCc3jmg/q4XSnd4m1F+1Z9PkezgUAAHNOQwMAAADzWqN02Xai1maSkq7bTbRnv6Gh5vBu4UYjn5rxHCUnzjgH0+cez5xrSN+qn+4SXJKhnNmLWe5epeS4jlUkV1981cXbejEXAAD0Cw0NAAAAzGvrNm74lyTf7BB+xMplp64qydMmCpbka+s2X/qF2avunnnKod3i40vKjGo44YQTlqTWl80kBzPjHs+ca0i/KruHuzU0pCTnHHvsscMznqdRTkmyoMuQv5vpHAAA0G80NAAAADDf1ZTSeduJUt7f5czZX50hSUl7e7f48A/bj5pJ/sV7Fr05SdeXwcwu93jmXEP61bqr1n0rySe7DHnYEUsf3G1ro/0aHR1tpNT/2WXIruGh4Q/MZA4AAOhHGhoAAACY9xp1fN10zmt3266ih2pt3NS1jqHyzOnmbq5ovjylvGG659Mb8+oe1yyei3zz6hoy75RS39UtXmt5ywtXvHDaDTPXfea61yR5eucC8pEPXfGhW6ebP0nvn20AAOgBDQ0AAADMe+s2Xfq5knx9iqd9qbWp9e+zUtA+aqP+V9d4ylubJzQfMZWcZz71zAXNFc03l5p3z6w6emHQ7nHZU+7sEn7CVJfP70W+QbuG3L+0l5S/L8k3ugx57O727g83m82FU8192vJTnpHUt3abvow3/nwyuXr9bAMAwGzT0AAAAMD9Qk2Z4moL5YBsN5EkrStbN9bkmi5DDi97ctlpJ5521P5yjY6ONprLm79x+xG3/VupeUuSSb2cWrJnweMnWy9TN2j3uDbqt7qEDzpiyeF/Ntlcvco3aNeQ+5dWqzXeTv53tzGl5Nhsy6dXrlj5xMnmba5ontlO45NJDuo8ql449tGxz04mX6+fbQAAmG06bgEAALhfKI0yVtv1jZMeX6baADEzpZaxlPrkzgPylPae8f8cWT7yjjpU3926ovWtJDVJVj131dLdQ9sfW0tj5LrPXPuikjx8qvO3azlr1XNX/cfOn9i5c88P9hx22VWX3Tz974aJDNQ93pVvpsvnyGvyuuaK5nGNms/W1B8mjUVJe/v6TRteN5v5Buoacr/T2tS6eGT5yAlJbXYaU5Kn1dr+/MjykQ+W2m61Dy6faLVau/Yec9JJJx22cNfQylrLS1O7bDNxl1uGy8Lfm3SRvX62AQBglmloAAAA4H5h7Mqxq0eWN7+S5HGTGP4fYxvHvjTbNe2t7qjvKkvyqiQP7TJscVLfWMbzxpHlzW0l+XatedCdZedhk1yE8bYkE+/hXspL7xze+dKyLe0Fw8NJMjTV74HuBuketz7e+sHI8uatSR7caUypeUJNnpCU3NU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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(\"image/png\", read(\"qualManhattanPlotOutput.png\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(\"image/png\", read(\"qualqq.png\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$\\bf{Quantitative}$ $\\bf{GWAS}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will now run the analysis on the same SNP dataset, but using a quantitative trait variable instead. For the quantiative analysis, we need to specific the quantitative variable on the left hand side in the\n",
    "\n",
    "`regression_formula` section of the .txt file (in our example, Trait).\n",
    "\n",
    "You also must specify the regression as linear instead of logistic on the \n",
    "   \n",
    "`regression` argument in the .txt file. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "#\n",
      "# Input and Output files.\n",
      "#\n",
      "plink_input_basename = gwasdata\n",
      "output_file = quantOutput.txt\n",
      "manhattan_plot_file = quantgwasManhattanPlotOutput.png\n",
      "qq_plot_file = quantqq.png\n",
      "output_table = quantresults.csv\n",
      "#\n",
      "# Analysis parameters for GWAS option.\n",
      "#\n",
      "regression = linear\n",
      "regression_formula = Trait ~ Sex\n"
     ]
    }
   ],
   "source": [
    ";cat quantControl.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " \n",
      " \n",
      "     Welcome to OpenMendel's\n",
      "      GWAS analysis option\n",
      "        version 0.5.0\n",
      " \n",
      " \n",
      "Reading the data.\n",
      "\n",
      "The current working directory is \"/Users/janets/Documents/lap_top_janet/janet/genetics/review_August2018/revision/OpenMendelTutorials/MendelGwas\".\n",
      "\n",
      "Keywords modified by the user:\n",
      "\n",
      "  affected_designator = 2\n",
      "  control_file = quantControl.txt\n",
      "  manhattan_plot_file = quantgwasManhattanPlotOutput.png\n",
      "  output_file = quantOutput.txt\n",
      "  output_table = quantresults.csv\n",
      "  pedigree_file = gwasdata.fam\n",
      "  plink_input_basename = gwasdata\n",
      "  qq_plot_file = quantqq.png\n",
      "  regression = linear\n",
      "  regression_formula = Trait ~ Sex\n",
      "  snpdata_file = gwasdata.bed\n",
      "  snpdefinition_file = gwasdata.bim\n",
      " \n",
      " \n",
      "Analyzing the data.\n",
      "\n",
      " \n",
      "Plots being drawn using MendelPlots package.\n",
      " \n",
      "Manhattan plot of GWAS results is in file: quantgwasManhattanPlotOutput.png\n",
      " \n",
      "QQ plot of GWAS results is in file: quantqq.png\n",
      " \n",
      " \n",
      "Mendel's analysis is finished.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "using MendelGWAS\n",
    "GWAS(\"quantControl.txt\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can check the output `.txt` file from the analysis. You can see that two SNPs had pvalues under the threshold, so their relevant information is displayed in the .txt file generated along with the regression results. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " \n",
      "Summary for Base Model with Formula: Trait ~ Sex\n",
      "Regression model: linear\n",
      "Link function: canonical\n",
      "Base components' effect estimates: \n",
      "   (Intercept) : 0.142482\n",
      "   Sex : -0.0129378\n",
      "Base model loglikelihood: -1258.177\n",
      " \n",
      " \n",
      "\n",
      "Summary for SNP rs1935681\n",
      " on chromosome 6 at basepair 112651205\n",
      "SNP p-value: 1.124e-11\n",
      "Minor allele frequency: 0.2523\n",
      "Hardy-Weinberg p-value: 0.3666\n",
      "SNP effect estimate: 0.2496\n",
      "SNP model loglikelihood: -1235.1273\n",
      "Proportion of base-model variance explained: 0.02074\n",
      " \n",
      "\n",
      "Summary for SNP rs2256412\n",
      " on chromosome 12 at basepair 41913108\n",
      "SNP p-value: 1.431e-34\n",
      "Minor allele frequency: 0.4741\n",
      "Hardy-Weinberg p-value: 0.1844\n",
      "SNP effect estimate: 0.3857\n",
      "SNP model loglikelihood: -1182.9861\n",
      "Proportion of base-model variance explained: 0.06607\n",
      " \n",
      " \n",
      " \n",
      "        P-value   Number of Passing\n",
      "FDR    Threshold     Predictors \n",
      "\n",
      "0.01    0.00000           2\n",
      "0.05    0.00000           2\n",
      "0.10    0.00000           2\n",
      "0.20    0.00009           5\n",
      "0.30    0.00021           8\n",
      "0.40    0.00048          14\n",
      "0.50    0.00048          14\n",
      "0.60    0.00091          19\n",
      "0.70    0.00177          29\n",
      "0.80    0.00274          39\n",
      "0.90    0.00564          65\n",
      " \n"
     ]
    }
   ],
   "source": [
    ";cat quantOutput.txt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To view the output file containing all SNPs and pvalues that was generated:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SNP,Chromosome,BasePair,Pvalue,NegLog10Pvalue\n",
      "rs3934834,1,1005805,0.9606754090532998,0.017423326035240563\n",
      "rs6603793,1,1505254,0.909143741049904,0.041367446800497865\n",
      "rs2843153,1,2245220,0.24546946624591717,0.6100025217308951\n",
      "rs7535528,1,2444413,0.5375925995318912,0.26954671838537847\n",
      "rs12046158,1,2891712,0.22439535221836035,0.6489861426334482\n",
      "rs2817134,1,3098714,0.3644891511102743,0.43831539377415935\n",
      "rs4494089,1,3254355,0.6866418028528727,0.16326976019414963\n",
      "rs4648505,1,3405295,0.09446386482644703,1.0247342899845668\n",
      "rs1181883,1,3677932,0.8758193397571711,0.05758546898965092\n"
     ]
    }
   ],
   "source": [
    ";head quantresults.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For benchmarking purposes, and to look at the total time of the analysis after precompliation we run the control file again. This time we include the time it takes to generate QQ and Manhattan Plots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " \n",
      " \n",
      "     Welcome to OpenMendel's\n",
      "      GWAS analysis option\n",
      "        version 0.5.0\n",
      " \n",
      " \n",
      "Reading the data.\n",
      "\n",
      "The current working directory is \"/Users/janets/Documents/lap_top_janet/janet/genetics/review_August2018/revision/OpenMendelTutorials/MendelGwas\".\n",
      "\n",
      "Keywords modified by the user:\n",
      "\n",
      "  affected_designator = 2\n",
      "  control_file = quantControl.txt\n",
      "  manhattan_plot_file = quantgwasManhattanPlotOutput.png\n",
      "  output_file = quantOutput.txt\n",
      "  output_table = quantresults.csv\n",
      "  pedigree_file = gwasdata.fam\n",
      "  plink_input_basename = gwasdata\n",
      "  qq_plot_file = quantqq.png\n",
      "  regression = linear\n",
      "  regression_formula = Trait ~ Sex\n",
      "  snpdata_file = gwasdata.bed\n",
      "  snpdefinition_file = gwasdata.bim\n",
      " \n",
      " \n",
      "Analyzing the data.\n",
      "\n",
      " \n",
      "Plots being drawn using MendelPlots package.\n",
      " \n",
      "Manhattan plot of GWAS results is in file: quantgwasManhattanPlotOutput.png\n",
      " \n",
      "QQ plot of GWAS results is in file: quantqq.png\n",
      " \n",
      " \n",
      "Mendel's analysis is finished.\n",
      "\n",
      " \n",
      " \n",
      "     Welcome to OpenMendel's\n",
      "      GWAS analysis option\n",
      "        version 0.5.0\n",
      " \n",
      " \n",
      "Reading the data.\n",
      "\n",
      "The current working directory is \"/Users/janets/Documents/lap_top_janet/janet/genetics/review_August2018/revision/OpenMendelTutorials/MendelGwas\".\n",
      "\n",
      "Keywords modified by the user:\n",
      "\n",
      "  affected_designator = 2\n",
      "  control_file = quantControl.txt\n",
      "  manhattan_plot_file = quantgwasManhattanPlotOutput.png\n",
      "  output_file = quantOutput.txt\n",
      "  output_table = quantresults.csv\n",
      "  pedigree_file = gwasdata.fam\n",
      "  plink_input_basename = gwasdata\n",
      "  qq_plot_file = quantqq.png\n",
      "  regression = linear\n",
      "  regression_formula = Trait ~ Sex\n",
      "  snpdata_file = gwasdata.bed\n",
      "  snpdefinition_file = gwasdata.bim\n",
      " \n",
      " \n",
      "Analyzing the data.\n",
      "\n",
      " \n",
      "Plots being drawn using MendelPlots package.\n",
      " \n",
      "Manhattan plot of GWAS results is in file: quantgwasManhattanPlotOutput.png\n",
      " \n",
      "QQ plot of GWAS results is in file: quantqq.png\n",
      " \n",
      " \n",
      "Mendel's analysis is finished.\n",
      "\n",
      " \n",
      " \n",
      "     Welcome to OpenMendel's\n",
      "      GWAS analysis option\n",
      "        version 0.5.0\n",
      " \n",
      " \n",
      "Reading the data.\n",
      "\n",
      "The current working directory is \"/Users/janets/Documents/lap_top_janet/janet/genetics/review_August2018/revision/OpenMendelTutorials/MendelGwas\".\n",
      "\n",
      "Keywords modified by the user:\n",
      "\n",
      "  affected_designator = 2\n",
      "  control_file = quantControl.txt\n",
      "  manhattan_plot_file = quantgwasManhattanPlotOutput.png\n",
      "  output_file = quantOutput.txt\n",
      "  output_table = quantresults.csv\n",
      "  pedigree_file = gwasdata.fam\n",
      "  plink_input_basename = gwasdata\n",
      "  qq_plot_file = quantqq.png\n",
      "  regression = linear\n",
      "  regression_formula = Trait ~ Sex\n",
      "  snpdata_file = gwasdata.bed\n",
      "  snpdefinition_file = gwasdata.bim\n",
      " \n",
      " \n",
      "Analyzing the data.\n",
      "\n",
      " \n",
      "Plots being drawn using MendelPlots package.\n",
      " \n",
      "Manhattan plot of GWAS results is in file: quantgwasManhattanPlotOutput.png\n",
      " \n",
      "QQ plot of GWAS results is in file: quantqq.png\n",
      " \n",
      " \n",
      "Mendel's analysis is finished.\n",
      "\n",
      " \n",
      " \n",
      "     Welcome to OpenMendel's\n",
      "      GWAS analysis option\n",
      "        version 0.5.0\n",
      " \n",
      " \n",
      "Reading the data.\n",
      "\n",
      "The current working directory is \"/Users/janets/Documents/lap_top_janet/janet/genetics/review_August2018/revision/OpenMendelTutorials/MendelGwas\".\n",
      "\n",
      "Keywords modified by the user:\n",
      "\n",
      "  affected_designator = 2\n",
      "  control_file = quantControl.txt\n",
      "  manhattan_plot_file = quantgwasManhattanPlotOutput.png\n",
      "  output_file = quantOutput.txt\n",
      "  output_table = quantresults.csv\n",
      "  pedigree_file = gwasdata.fam\n",
      "  plink_input_basename = gwasdata\n",
      "  qq_plot_file = quantqq.png\n",
      "  regression = linear\n",
      "  regression_formula = Trait ~ Sex\n",
      "  snpdata_file = gwasdata.bed\n",
      "  snpdefinition_file = gwasdata.bim\n",
      " \n",
      " \n",
      "Analyzing the data.\n",
      "\n",
      " \n",
      "Plots being drawn using MendelPlots package.\n",
      " \n",
      "Manhattan plot of GWAS results is in file: quantgwasManhattanPlotOutput.png\n",
      " \n",
      "QQ plot of GWAS results is in file: quantqq.png\n",
      " \n",
      " \n",
      "Mendel's analysis is finished.\n",
      "\n",
      " \n",
      " \n",
      "     Welcome to OpenMendel's\n",
      "      GWAS analysis option\n",
      "        version 0.5.0\n",
      " \n",
      " \n",
      "Reading the data.\n",
      "\n",
      "The current working directory is \"/Users/janets/Documents/lap_top_janet/janet/genetics/review_August2018/revision/OpenMendelTutorials/MendelGwas\".\n",
      "\n",
      "Keywords modified by the user:\n",
      "\n",
      "  affected_designator = 2\n",
      "  control_file = quantControl.txt\n",
      "  manhattan_plot_file = quantgwasManhattanPlotOutput.png\n",
      "  output_file = quantOutput.txt\n",
      "  output_table = quantresults.csv\n",
      "  pedigree_file = gwasdata.fam\n",
      "  plink_input_basename = gwasdata\n",
      "  qq_plot_file = quantqq.png\n",
      "  regression = linear\n",
      "  regression_formula = Trait ~ Sex\n",
      "  snpdata_file = gwasdata.bed\n",
      "  snpdefinition_file = gwasdata.bim\n",
      " \n",
      " \n",
      "Analyzing the data.\n",
      "\n",
      " \n",
      "Plots being drawn using MendelPlots package.\n",
      " \n",
      "Manhattan plot of GWAS results is in file: quantgwasManhattanPlotOutput.png\n",
      " \n",
      "QQ plot of GWAS results is in file: quantqq.png\n",
      " \n",
      " \n",
      "Mendel's analysis is finished.\n",
      "\n",
      " \n",
      " \n",
      "     Welcome to OpenMendel's\n",
      "      GWAS analysis option\n",
      "        version 0.5.0\n",
      " \n",
      " \n",
      "Reading the data.\n",
      "\n",
      "The current working directory is \"/Users/janets/Documents/lap_top_janet/janet/genetics/review_August2018/revision/OpenMendelTutorials/MendelGwas\".\n",
      "\n",
      "Keywords modified by the user:\n",
      "\n",
      "  affected_designator = 2\n",
      "  control_file = quantControl.txt\n",
      "  manhattan_plot_file = quantgwasManhattanPlotOutput.png\n",
      "  output_file = quantOutput.txt\n",
      "  output_table = quantresults.csv\n",
      "  pedigree_file = gwasdata.fam\n",
      "  plink_input_basename = gwasdata\n",
      "  qq_plot_file = quantqq.png\n",
      "  regression = linear\n",
      "  regression_formula = Trait ~ Sex\n",
      "  snpdata_file = gwasdata.bed\n",
      "  snpdefinition_file = gwasdata.bim\n",
      " \n",
      " \n",
      "Analyzing the data.\n",
      "\n",
      " \n",
      "Plots being drawn using MendelPlots package.\n",
      " \n",
      "Manhattan plot of GWAS results is in file: quantgwasManhattanPlotOutput.png\n",
      " \n",
      "QQ plot of GWAS results is in file: quantqq.png\n",
      " \n",
      " \n",
      "Mendel's analysis is finished.\n",
      "\n",
      " \n",
      " \n",
      "     Welcome to OpenMendel's\n",
      "      GWAS analysis option\n",
      "        version 0.5.0\n",
      " \n",
      " \n",
      "Reading the data.\n",
      "\n",
      "The current working directory is \"/Users/janets/Documents/lap_top_janet/janet/genetics/review_August2018/revision/OpenMendelTutorials/MendelGwas\".\n",
      "\n",
      "Keywords modified by the user:\n",
      "\n",
      "  affected_designator = 2\n",
      "  control_file = quantControl.txt\n",
      "  manhattan_plot_file = quantgwasManhattanPlotOutput.png\n",
      "  output_file = quantOutput.txt\n",
      "  output_table = quantresults.csv\n",
      "  pedigree_file = gwasdata.fam\n",
      "  plink_input_basename = gwasdata\n",
      "  qq_plot_file = quantqq.png\n",
      "  regression = linear\n",
      "  regression_formula = Trait ~ Sex\n",
      "  snpdata_file = gwasdata.bed\n",
      "  snpdefinition_file = gwasdata.bim\n",
      " \n",
      " \n",
      "Analyzing the data.\n",
      "\n",
      " \n",
      "Plots being drawn using MendelPlots package.\n",
      " \n",
      "Manhattan plot of GWAS results is in file: quantgwasManhattanPlotOutput.png\n",
      " \n",
      "QQ plot of GWAS results is in file: quantqq.png\n",
      " \n",
      " \n",
      "Mendel's analysis is finished.\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "BenchmarkTools.Trial: \n",
       "  memory estimate:  1.02 GiB\n",
       "  allocs estimate:  7908784\n",
       "  --------------\n",
       "  minimum time:     3.451 s (13.34% GC)\n",
       "  median time:      3.575 s (15.41% GC)\n",
       "  mean time:        3.575 s (15.41% GC)\n",
       "  maximum time:     3.699 s (17.34% GC)\n",
       "  --------------\n",
       "  samples:          2\n",
       "  evals/sample:     1"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#using BenchmarkTools\n",
    "@benchmark GWAS(\"quantControl.txt\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we examine the results by looking at the Manhattan and QQ plots.  The qualitative trait is just a thresholded transformation (a dichotomized version) of the quantitative traits so as you would predict, the quantitative trait's results are more significant than the qualitative trait's results. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(\"image/png\", read(\"quantgwasManhattanPlotOutput.png\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(\"image/png\", read(\"quantqq.png\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusions\n",
    "\n",
    "MendelGWAS is a very fast and efficient way to conduct a GWAS.  Note that although we didn't include them in these analyses, MendelGWAS has the option of generating and including principal components as fixed effects inthe analysis. If you have time see if you can modify the control files to include 2 pcs and rerun the analyses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Julia 1.1.0",
   "language": "julia",
   "name": "julia-1.1"
  },
  "language_info": {
   "file_extension": ".jl",
   "mimetype": "application/julia",
   "name": "julia",
   "version": "1.1.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}