The F-SNP database gathers computationally predicted functional information about SNPs, particularly aiming to facilitate identification of disease-causing SNPs in association studies. Due to the large overhead of large-scale genotyping and analysis, it is often required, when conducting association studies, to prioritize SNPs in a target genomic region based on their potential functional effects (1). Typically, SNPs occurring in functional genomic regions such as protein coding or regulatory regions are more likely to cause functional distortion and, as such, more likely to underlie disease-causing variations. Current bioinformatics tools examine the functional effects of SNPs only with respect to a single biological function. Therefore, much time and effort is required from researchers to separately use multiple tools and interpret the (often conflicting) predictions.
