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

Yan Wen; Jingcan Hao; Xiong Guo; Xiao Xiao; Cuiyan Wu; Sen Wang; Tielin Yang; Hui Shen; Xiangding Chen; Lijun Tan; Qing Tian; Hong-Wen Deng; Feng Zhang

doi:10.1016/j.jbi.2015.06.025

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

J Biomed Inform. 2015 Oct:57:38-41. doi: 10.1016/j.jbi.2015.06.025. Epub 2015 Jul 15.

Authors

Yan Wen¹, Jingcan Hao¹, Xiong Guo¹, Xiao Xiao¹, Cuiyan Wu¹, Sen Wang¹, Tielin Yang², Hui Shen³, Xiangding Chen⁴, Lijun Tan⁴, Qing Tian³, Hong-Wen Deng³, Feng Zhang⁵

Affiliations

¹ Key Laboratory of Trace Elements and Endemic Diseases of Ministry of Health, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China.
² Key Laboratory of Biomedical Information Engineering of Ministry of Education, and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, PR China.
³ Department of Biostatistics and Bioinformatics, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA; Center for Bioinformatics and Genomics, Tulane University, New Orleans, LA, USA.
⁴ Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, PR China.
⁵ Key Laboratory of Trace Elements and Endemic Diseases of Ministry of Health, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China. Electronic address: [email protected].

PMID: 26188273
DOI: 10.1016/j.jbi.2015.06.025

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.

Keywords: Genome-wide association studies; Genotype independence analysis; SWGDT; Sliding window.

MeSH terms

Cartilage, Articular
Genetic Predisposition to Disease
Genome-Wide Association Study*
Genotype*
Humans
Kashin-Beck Disease / genetics*
Statistics as Topic