ABSTRACT With the rapid advancement of genome‐wide association studies (GWAS), downstream analyses of GWAS data have become essential for elucidating the genetic mechanisms that underlie complex diseases. However, current post‐GWAS analyses face numerous challenges, including heterogeneous data formats, challenges in multi‐omics integration, and increasingly complex analytical workflows. As a comprehensive post‐GWAS analysis software platform, Omics GWAS provides researchers with an automated, end‐to‐end solution spanning data preparation through results’ visualization by integrating functional modules such as data standardization, Mendelian randomization, multi‐omics joint analysis, comorbidity mechanism exploration, and drug target discovery. The platform supports conversion of GWAS summary statistics across diverse data sources, integrates multidimensional omics data including expression quantitative trait loci (eQTLs), protein quantitative trait loci (pQTLs), and methylation quantitative trait loci (mQTLs) and systematically investigates causal relationships between genotypes and phenotypes using methods such as Mendelian randomization, colocalization analysis, and summary data–based Mendelian randomization (SMR). The modular design of Omics GWAS not only significantly improves analytical efficiency and the reproducibility of results but also offers robust technical support for precision medicine research and drug target development.
Zhang et al. (Thu,) studied this question.