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Compositional analysis of microbiome data using the linear decomposition model (LDM).
Hu, Yi-Juan; Satten, Glen A.
Afiliação
  • Hu YJ; Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, United States.
  • Satten GA; Department of Gynecology and Obstetrics, Emory University School of Medicine, Atlanta, GA 30322, United States.
Bioinformatics ; 39(11)2023 11 01.
Article em En | MEDLINE | ID: mdl-37930883
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Microbiota Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Microbiota Idioma: En Ano de publicação: 2023 Tipo de documento: Article