Compositional analysis of microbiome data using the linear decomposition model (LDM)
Author:
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
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
Link
https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btad668/52762454/btad668.pdf
Reference20 articles.
1. The Statistical Analysis of Compositional Data
2. Testing for differential abundance in compositional counts data, with application to microbiome studies;Brill;Ann Appl Stat,2022
3. benchdamic: benchmarking of differential abundance methods for microbiome data;Calgaro;Bioinformatics,2023
4. Unifying the analysis of high-throughput sequencing datasets: characterizing RNA-seq, 16S rRNA gene sequencing and selective growth experiments by compositional data analysis;Fernandes;Microbiome,2014
5. Microbiome datasets are compositional: and this is not optional;Gloor;Front Microbiol,2017
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