Rank normalization empowers a t-test for microbiome differential abundance analysis while controlling for false discoveries.

ABSTRACT: A major task in the analysis of microbiome data is to identify microbes associated with differing biological conditions. Before conducting analysis, raw data must first be adjusted so that counts from different samples are comparable. A typical approach is to estimate normalization factors by which all counts in a sample are multiplied or divided. However, the inherent variation associated with estimation of normalization factors are often not accounted for in subsequent analysis, leading to a loss of precision. Rank normalization is a nonparametric alternative to the estimation of normalization factors in which each count for a microbial feature is replaced by its intrasample rank. Although rank normalization has been successfully applied to microarray analysis in the past, it has yet to

SUBMITTER: Davis ML 

PROVIDER: S-EPMC9630402 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature