Following the successful development of i-GSEA4GWAS which is an open platform for pathway-based analysis (PBA) of genome-wide association study (GWAS) data, the team led by Prof Wang Jing from the Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences developed another web server named ICSNPathway (Identify candidate causal SNPs and pathways) to solve the problemfor GWAS data interpretation within one analytical framework. Different fromprevious products, ICSNPathway integrated the linkage disequilibrium (LD) analysis, functional SNP annotation and PBA to identify candidatescausal SNPs and their corresponding candidate causal pathways, which provides novel insights and clues for future research on mechanisms of complex diseases and traits.

GWAS is widely utilized to identify genes involved in human complex disease or some other trait. One key challenge for GWAS data interpretation is to identify causal SNPs and provide profound evidence on how they affect the trait. Currently, researches are focusing on identification of candidate causal variants from the most significant SNPs of GWAS, while there is lack of support on biological mechanisms as represented by pathways. Although PBA has been designed to identify disease-related pathways by analyzing the full list of SNPs from GWAS, it does not emphasize on interpreting causal SNPs. To our knowledge, so far there is no web server available to solve the problem for GWAS data interpretation within one analytical framework.

ICSNPathway is developed to identify candidates causal SNPs and their corresponding candidate causal pathways from GWAS by integrating linkage disequilibrium (LD) analysis, functional SNP annotation and PBA. ICSNPathway aims to facilitate researchers to answer the questions that what the candidate causal SNPs are and through which biological mechanism(s) they affect the trait. Thus it provides a feasible solution to bridge the gap between GWAS and disease mechanism study by generating hypothesis of SNP -> gene -> pathway(s). The ICSNPathway server is freely available at http://icsnpathway.psych.ac.cn/.

The project was funded by the Knowledge Innovation Project of the Chinese Academy of Sciences (KSCX2-EW-J-8) and the Project for Young Scientists Fund, Institute of Psychology, Chinese Academy of Sciences (O9CX115011).

The study has been published in Nucleic Acids Research:
Zhang, K., Chang, S., Cui, S., Guo, L., Zhang, L. and Wang, J. (2011) ICSNPathway: identify candidate causal SNPs and pathways from genome-wide association study by one analytical framework. Nucleic Acids Res, 39 Suppl 2, W437-443.