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

• DOI: 10.1093/bioinformatics/btac438
• Publication Date: 2022-06-30T15:53:25Z
• Authors: Yang Cao; Qingyang Dong; Dan Wang; Pengcheng Zhang; Ying Liu; Chao Niu
• Keywords: 0303 health sciences; 03 medical and health sciences; Microbiota; Software; Biomarkers; 3. Good health

AbstractSummaryCharacterizing 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 implementationmicrobiomeMarker 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 informationSupplementary data are available at Bioinformatics online.