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postGWAS: A web server for deciphering the causality post the genome-wide association studies.

Computers in biology and medicine - 1 Mar 2024

Wang Tao, Yan Zhihao, Zhang Yiming, Lou Zhuofei, Zheng Xiaozhu, Mai DuoDuo, Wang Yongtian, Shang Xuequn, Xiao Bing, Peng Jiajie, Chen Jing

Abstract excerpt

While genome-wide association studies (GWAS) have unequivocally identified vast disease susceptibility variants, a majority of them are situated in non-coding regions and are in high linkage disequilibrium (LD). To pave the way of translating GWAS signals to clinical drug targets, it is essential to identify the underlying causal variants and further causal genes. To this end, a myriad of post-GWAS methods have...

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PMID: 38359659
DOI: 10.1016/j.compbiomed.2024.108108

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