microbiomeMarker: an R/Bioconductor package for microbiome marker identification and visualization

Abstract Summary Characterizing biomarkers based on microbiome profiles has great potential for translational medicine and precision medicine. Here, we present microbiomeMarker, an R/Bioconductor package implementing commonly used normalization and differential analysis (DA) methods, and three super...

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Bibliographic Details
Published in:Bioinformatics Vol. 38; no. 16; pp. 4027 - 4029
Main Authors: Cao, Yang, Dong, Qingyang, Wang, Dan, Zhang, Pengcheng, Liu, Ying, Niu, Chao
Format: Journal Article
Language:English
Published: England Oxford University Press 10.08.2022
Subjects:
Biomarkers
Microbiota
Software
ISSN:1367-4803, 1367-4811, 1460-2059, 1367-4811
Online Access:Get full text
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Summary:Abstract Summary Characterizing biomarkers based on microbiome profiles has great potential for translational medicine and precision medicine. Here, we present microbiomeMarker, an R/Bioconductor package implementing commonly used normalization and differential analysis (DA) methods, and three supervised learning models to identify microbiome markers. microbiomeMarker also allows comparison of different methods of DA and confounder analysis. It uses standardized input and output formats, which renders it highly scalable and extensible, and allows it to seamlessly interface with other microbiome packages and tools. In addition, the package provides a set of functions to visualize and interpret the identified microbiome markers. Availability and implementation microbiomeMarker is freely available from Bioconductor (https://www.bioconductor.org/packages/microbiomeMarker). Source code is available and maintained at GitHub (https://github.com/yiluheihei/microbiomeMarker). Supplementary information Supplementary data are available at Bioinformatics online.
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ISSN:1367-4803
1367-4811
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btac438