MbDecoda: a debiased approach to compositional data analysis for microbiome surveys.

ABSTRACT: Potentially pathogenic or probiotic microbes can be identified by comparing their abundance levels between healthy and diseased populations, or more broadly, by linking microbiome composition with clinical phenotypes or environmental factors. However, in microbiome studies, feature tables provide relative rather than absolute abundance of each feature in each sample, as the microbial loads of the samples and the ratios of sequencing depth to microbial load are both unknown and subject to considerable variation. Moreover, microbiome abundance data are count-valued, often over-dispersed and contain a substantial proportion of zeros. To carry out differential abundance analysis while addressing these challenges, we introduce mbDecoda, a model-based approach for debiased analysis of sparse com

SUBMITTER: Zong Y 

PROVIDER: S-EPMC11066923 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature