Our web server implements i-GSEA for GWAS data analysis to explore the biological function and mechanism from a systems point of view. It is efficient not only for in-house GWASs with available genotype data, but also for secondary data mining of published GWASs, where genotype data are not readily available. i-GSEA4GWAS aims to help researchers take the best advantage of the high-cost GWAS data to look for new biological insights worthy of further confirmation. This represents the major potential for i-GSEA4GWAS. The improved i-GSEA approach, the optimal multiple-level SNPs->genes mapping system, the comprehensive pathway/gene set database with options of customization, as well as the consideration of MHC/xMHC region distinguish i-GSEA4GWAS from other programs. It should be noted that i-GSEA4GWAS does not take into account the linkage disequilibrium (LD) patterns from SNP arrays and would not prune the set of SNPs for LD since these can only be done when genotype data is available. So, users are recommended to input SNPs not in LD (say r2 < 0.2) to reduce the possibility of biased results due to LD patterns from SNP
