DANUBE: Data-driven meta-ANalysis using UnBiased Empirical distributions-applied to biological pathway analysis.

ABSTRACT: Identifying the pathways and mechanisms that are significantly impacted in a given phenotype is challenging. Issues include patient heterogeneity and noise. Many experiments do not have a large enough sample size to achieve the statistical power necessary to identify significantly impacted pathways. Meta-analysis based on combining p-values from individual experiments has been used to improve power. However, all classical meta-analysis approaches work under the assumption that the p-values produced by experiment-level statistical tests follow a uniform distribution under the null hypothesis. Here we show that this assumption does not hold for three mainstream pathway analysis methods, and significant bias is likely to affect many, if not all such meta-analysis studies. We introduce DANUBE,

SUBMITTER: Nguyen T 

PROVIDER: S-EPMC5919277 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature