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i-GSEA4GWAS v2 (improved GSEA for GWAS v2) is an important expansion of i-GSEA4GWAS . In comparison to i-GSEA4GWAS, which applies a pathway-based analysis (PBA) approach named i-GSEA (improved gene set enrichment analysis) to analyze genome-wide association study (GWAS) SNP P-values to identify pathways associated with traits. i-GSEA4GWAS v2 is featured by implementing both i-GSEA and follow-up functinal analysis of SNPs in trait-associated pathways. The functional analysis of SNPs is performed based on Ensembl putative functional SNP annotation data  to annotate the coding feature of SNPs and by using ENCODE regulatory regions  to annotate the non-coding feature of SNPs. Expression quantitative trait loci (eQTLs) related to the SNPs were also annotated. The functional analysis will help to select putative functional SNPs as candidate causal SNPs for further validation research. To our knowledge, this is the first effort that the functional analysis of SNPs is implemented in a PBA tool for GWAS.
Input, processing, and output
With the GWAS SNP association values as input, the program firstly performs i-GSEA to identify pathway correlated to trait. Then it carries out functional analysis for the both the most significant SNPs of the genes involved in the pathways and their linkage disequilibrium (LD) proxies extracted from HapMap populations  or 1000 Genome . The functional analysis includes annotation and enrichment analysis. The first type of annotation is to annotate SNPs implacting protein function (deleterious or probably/possibly damaging non-synonymous, or others including splice donor variant, stop lost, incomplete terminal codon variant, inframe insertion, transcript ablation, splice acceptor variant, frameshift variant, stop gained, initiator codon variant, splice region variant or inframe deletion) . The second type of annotation is to map SNPs to ENCODE regulatory feature peaks , including DNase-seq peaks of open chromatin, FAIRE peaks of open chromatin, TFBS SPP-based peaks, TFBS PeakSeq-based peaks and Histone peaks from ENCODE Analysis Hub. The third type of annotation is to annotate SNP related eQTL. The enrichment analysis is implemented for each type of functional elements to explore if the significant SNPs in each trait-associated pathway are significantly enriched in these functional elements. Finally, the trait-associated pathways with detailed results of functional analysis are displayed.
1. Since computation for i-GSEA and functional analysis will take some time (e.g. 23 minutes for demo data sets),
to facilitate users to access the results, i-GSEA4GWAS v2 provides a web link to results upon data
submission. The link will also briefly report the running status of the job. Users can bookmark the link to
access results at a later time. Moreover, an e-mail with result notification will be sent automatically if users
provide an email address.
Copyright: Bioinformatics Lab, Institute of Psychology, Chinese Academy of Sciences
Last update: May 14, 2014