Compositional analysis of microbiome data using the linear decomposition model (LDM)

Author:

Hu Yi-Juan1ORCID,Satten Glen A2

Affiliation:

1. Department of Biostatistics and Bioinformatics, Emory University , Atlanta, GA 30322, United States

2. Department of Gynecology and Obstetrics, Emory University School of Medicine , Atlanta, GA 30322, United States

Abstract

Abstract Summary There are compelling reasons to test compositional hypotheses about microbiome data. We present here linear decomposition model-centered log ratio (LDM-clr), an extension of our LDM approach to allow fitting linear models to centered-log-ratio-transformed taxa count data. As LDM-clr is implemented within the existing LDM program, this extension enjoys all the features supported by LDM, including a compositional analysis of differential abundance at both the taxon and community levels, while allowing for a wide range of covariates and study designs for either association or mediation analysis. Availability and implementation LDM-clr has been added to the R package LDM, which is available on GitHub at https://github.com/yijuanhu/LDM.

Funder

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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