The impact of violating the independence assumption in meta-analysis on biomarker discovery.

ABSTRACT: With rapid advancements in high-throughput sequencing technologies, massive amounts of "-omics" data are now available in almost every biomedical field. Due to variance in biological models and analytic methods, findings from clinical and biological studies are often not generalizable when tested in independent cohorts. Meta-analysis, a set of statistical tools to integrate independent studies addressing similar research questions, has been proposed to improve the accuracy and robustness of new biological insights. However, it is common practice among biomarker discovery studies using preclinical pharmacogenomic data to borrow molecular profiles of cancer cell lines from one study to another, creating dependence across studies. The impact of violating the independence assumption in meta-an

SUBMITTER: Abbas-Aghababazadeh F 

PROVIDER: S-EPMC9885264 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature