First, our server maps SNPs to the genome-wide genes. i-GSEA4GWAS contains an optional multiple-level broad-to-narrow SNPs->genes mapping system, which helps users either fully explore genome-wide SNP data (by choosing ‘500-kb upstream and downstream of gene’) or narrow down the research scope by only focusing on functional SNPs (by choosing ‘functional SNP’). The SNPs->genes mapping is established based on SNP and gene annotations from the Ensembl BioMart database (Release 56–15 September 2009, http://www.ensembl.org/biomart/martview) (21). Next, the program uses the list of SNP-mapped genes to filter the collection of pathways/gene sets to obtain candidate pathways/gene sets. Additional filtering includes a keyword search to define the function of gene sets, to mask major histocompatibility complex/extended major histocompatibility complex (MHC/xMHC) region (22) to only explore the non-MHC/xMHC region (23), and to restrain gene set size to avoid overly narrow or overly broad functional categories and too large a search space, with the default parameter of minimum 20 and maximum 200 (3,9). Then i-GSEA4GWAS performs i-GSEA to identify pathways/gene sets correlated with traits. When the job is running, the progress of the three key steps (mapping, permutation and statistical analysis) will be shown in the progress bar.
