GSAA (Gene Set Association Analysis) is a computational method that integrates gene expression analysis with genome wide association studies to determine whether an a priori defined sets of genes shows statistically significant, concordant differences with respect to gene expression profiles and genotypes between two biological states. Gene sets are generally a group of genes that are putatively functionally related, co-regulated, or tightly linked on the same chromosome.
GSAA-SNP (Gene Set Association Analysis-SNP) is a computational method that determines whether an a priori defined sets of genes shows statistically significant, concordant differences with respect to genotypes between two biological states. Gene sets are generally a group of genes that are putatively functionally related, co-regulated, or tightly linked on the same chromosome.
GSAA-Seq (Gene Set Association Analysis for RNA-Seq) is a computational method that evaluates whether an a priori defined sets of genes shows statistically significant, concordant differences with respect to RNA-Seq gene expression profiles between two biological states. Gene sets are generally a group of genes that are putatively functionally related, co-regulated, or tightly linked on the same chromosome.