PAST

PAST takes GWAS output and assigns SNPs to genes, uses those genes to find pathways associated with the genes, and plots pathways based on significance.

Key Features:

• SNP-to-gene assignment: Assigns SNPs from GWAS output to genes.
• Pathway association: Uses assigned genes to find pathways associated with those genes.
• Enrichment calculation: Calculates enrichment score and significance of pathways.
• Visualization: Plots pathways based on significance.
• GWAS data input: Implements methods for reading GWAS input data.
• Parallel processing: Processes data in parallel to reduce analysis time.

Scientific Applications:

• GWAS interpretation: Interprets genome-wide association study data using metabolic pathway analysis to find biological mechanisms associated with traits of interest.
• Plant phenotypic trait analysis: Identifies significant pathways and mechanisms explaining phenotypic traits of interest in plants.
• Genetic architecture elucidation: Associates metabolic pathways with GWAS datasets to better understand the genetic architecture and mechanisms affecting phenotypes.

Methodology:

PAST implements methods for reading GWAS input data, finding genes associated with SNPs, calculating enrichment score and significance of pathways, and plotting pathways.