SWGDT: A sliding window-based genotype dependence testing tool for genome-wide susceptibility gene scan

Abstract

Genome-wide association studies (GWAS) are a powerful tool for pathogenetic studies of complex diseases. The rich genetic information of GWAS data is mostly not fully utilized. In this study, we developed a sliding window-based genotype dependence testing tool SWGDT. SWGDT can be applied to GWAS data for genome-wide susceptibility gene scan utilizing known causal gene information. To evaluate the performance of SWGDT, a real GWAS dataset of Kashin-Beck disease (KBD) was analyzed. Immunohistochemistry was also performed to validate the relevance of identified gene with KBD. SWGDT analysis of KBD GWAS data identified a novel candidate gene TACR1 for KBD. Immunohistochemistry observed that the expression level of TACR1 protein in KBD articular cartilage was significantly higher than that in healthy articular cartilage. The real GWAS data analysis results illustrate the performance of SWGDT for genome-wide susceptibility gene scan. SWGDT can help to identify novel disease genes that may be missed by GWAS.