najlaksouri / gwas-workflow

GWAS-Workflow

Performing a Genome-Wide Association Studies (GWAS) can be a laborious task. In this reporsitory, we describe the pipeline that we have adapted to carry on a GWAS analysis using ddRAD-seq-derived SNPs. Underneath this README, we illustrate the different steps needed to run the analysis and we provide the codes necessary to reproduce this work.

Prerequisites

• Stacks
• BWA-Mem
• SAMtools
• BCFtools
• GATK-HaplotypeCaller
• Freebayes
• Plink
• R program and RStudio Desktop:
  • ggplot
  • GAPIT
  • CMplot
  • SmartPCA

Content

Step 1. ddRAD-Sequencing

Step 2. Data processing

• De-multiplexing: ------------------------> stacks.sh
• QC filtering: ------------------------> trimmomatic.sh
• Remove duplicated reads ------------------------> dedup.sh
• Reads mapping: ------------------------> align_bwa.mk

Step 3. Variant calling and filtering

• BCFtools calling: ------------------------> bcftoolsCall.mk
• Freebayes calling: ------------------------> freebayesCall.mk
• GATK calling: ------------------------> gatkCall.mk
• MAF filtering anf imputation: ------------------------> maf_imputation.mk

Step 4. GWAS analysis

• Phenotypic data assessement ------------------------> trait transformations
• PCA analysis
• Relatedness
• Statistical model assessment

Reference

That's it.... Good luck!