Meta-analysis methods for multiple related markers: Applications to microbiome studies with the results on multiple α-diversity indices.

ABSTRACT: Meta-analysis is a practical and powerful analytic tool that enables a unified statistical inference across the results from multiple studies. Notably, researchers often report the results on multiple related markers in each study (eg, various α-diversity indices in microbiome studies). However, univariate meta-analyses are limited to combining the results on a single common marker at a time, whereas existing multivariate meta-analyses are limited to the situations where marker-by-marker correlations are given in each study. Thus, here we introduce two meta-analysis methods, multi-marker meta-analysis (mMeta) and adaptive multi-marker meta-analysis (aMeta), to combine multiple studies throughout multiple related markers with no priori results on marker-by-marker correlations. mMeta is a st

SUBMITTER: Koh H 

PROVIDER: S-EPMC8325033 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature