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Tutorial to run GWAS including the X chromosome

  • This tutorial will cover the following steps, all including the autosomes and the X chromosome:
    • Quality control of genotype data
    • Imputation of genotype data
    • Genome-wide association study (GWAS)
  • Genotype data is provided to use with this tutorial, or you can run through it using your own genotype data

Getting Started

Clone the repository

  • Clone this repository to get a local copy of all files

  • In your terminal or HPC environment navigate to the location you would like to download a copy of all the files in this tutorial

  • Then run the following code:

git clone https://github.com/jodithea/Tutorial_GWAS_including_X_chromosome.git
  • You will now have a copy of all of the directories and files from this tutorial

Software needed

  • For this tutorial you will need the following software
    • Plink v1.9
    • R (v4.5.0 is used in this tutorial)
      • Make sure the R package 'tidyverse' is installed
    • vcftools (v0.1.16 used in this tutorial)
    • bcftools (v1.22 used in this tutorial)
    • GCTA (v1.94.1 used in this tutorial)

How to use this tutorial

  • Follow through the directories and files in chronological order

Markdown files

  • Markdown files (files ending with .md) contain instructions and documentation
  • You can view these files directly in the GitHub web interface
  • Or, if you have a local clone of the repository, you can view them in the terminal using cat, e.g.:
 cat README.md

Scripts

  • Scripts (i.e. files ending with '.sh') are shell scripts that can be submitted to your HPC environment
  • Again you can view these files directly in the GitHub web interface or in your local clone of the repository by using cat
  • All scripts in this repository follow a similar layout:
  1. Shebang and Scheduler Header
    • Every script starts with a shebang (#!/bin/bash) to indicate it is a bash script, followed by HPC scheduler directives
    • The schedular directives are written for PBS, for example:
#!/bin/bash
#PBS -l walltime=00:10:00
#PBS -l mem=1GB
#PBS -l ncpus=1

If you use SLURM instead of PBS, you can replace these lines with SLURM directives, for example:

#!/bin/bash
#SBATCH --time=00:10:00
#SBATCH --mem=1GB
#SBATCH --cpus-per-task=1

To do this replacement, in your local clone of the repository, open the script with an editor, for example:

nano 01_Split_X_chromosome.sh

Then edit the scheduler directives in the file as needed

  1. Script Description

    • A short comment explaining what the script does, for example:
# This script splits the X chromosome into non-pseudoautosomal region (nPAR) (coded as CHR 23) and pseudoautosomal region (PAR) (coded as CHR 25)

  1. Environment

    • This section loads any required modules or software, for example:
### Environment ###
module load plink/1.90b7

  1. Preamble / User Variables

    • This section defines any directories, file paths, or parameters used in the script
    • You need to edit this section of the script as appropriate
    • For example, in each script the 'directory' variable is defined. Open the script using 'nano' (or a similar editor) and set the path to the location of where your local clone of the repository is
### Preamble ###
# Update to point to the location where you are doing this tutorial
directory=/path/Tutorial_GWAS_including_X_chromosome/

  1. Commands / Submission Section

    • This section contains the actual commands that perform the work
    • For example:
### Submit script ###
cd ${directory}

# Split chromosome X
plink --bfile 01_Genotype_Data/Genotypes_chrX \
      --split-x b37 \
      --make-bed \
      --out 01_Genotype_Data/Genotypes_chrX_split

Submitting scripts

  • After viewing the script and making any edits as appropriate, submit the script

For PBS, submit using qsub, e.g.:

qsub 01_Split_X_chromosome.sh

For SLURM (and after you have edited the scheduler directives appropriately), submit using sbatch, e.g.:

sbatch 01_Split_X_chromosome.sh
  • You can check the status of your jobs:

For PBS, using qstat:

qstat -u your_username

For SLURM, using squeue:

squeue -u your_username

Job Arrays (PBS vs SLURM)

  • Some scripts in this tutorial use job arrays, one job per chromosome:

    • 03_Imputation/04_Convert_and_filter_imputed_genotype_data.sh
    • 04_Ancestry_Checks/02_Tidy_1000G_data.sh
    • 04_Ancestry_Checks/03_Merge_1000G_with_tutorial_data_and_prune.sh

  • The scripts are written using PBS job scheduling

PBS job arrays

  • The PBS scheduler directive uses #PBS -J to define the range of array jobs, for example:
#!/bin/bash
#PBS -l walltime=01:00:00
#PBS -l mem=80GB
#PBS -l ncpus=1
#PBS -J 1-22
  • Within the script, the array index for the current task is accessed using PBS_ARRAY_INDEX, for example:
chr=${PBS_ARRAY_INDEX}
  • Another example from this tutorial:
files=(${directory}03_Imputation/Genotype_imputation_results/chr_*.zip)
chr=$(basename "${files[$PBS_ARRAY_INDEX]}" .zip)

SLURM job arrays

  • If your HPC system uses SLURM, you must modify these scripts

  • Open the script using 'nano' (or a similar editor) and replace the PBS array directive with:

#!/bin/bash
#SBATCH --time=01:00:00
#SBATCH --mem=80GB
#SBATCH --cpus-per-task=1
#SBATCH --array=1-22
  • And inside the script replace PBS_ARRAY_INDEX with the SLURM equivalent:
chr=${SLURM_ARRAY_TASK_ID}
files=(${directory}03_Imputation/Genotype_imputation_results/chr_*.zip)
chr=$(basename "${files[$SLURM_ARRAY_TASK_ID]}" .zip)