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

Author:

Cao Yang1ORCID,Dong Qingyang1,Wang Dan2,Zhang Pengcheng1,Liu Ying1,Niu Chao1

Affiliation:

1. Department of Environmental Medicine, Tianjin Institute of Environmental and Operational Medicine , Tianjin 300050, China

2. BioMap (Beijing) Intelligence Technology Limited , Beijing 100005, China

Abstract

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.

Funder

Tianjin Institute of Environmental and Operational Medicine

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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