MetaMarker: A pipeline for de novo discovery of novel metagenomic biomarkers

Mohamad Koohi-Moghadam; Mitesh J. Borad; Nhan L. Tran; Kristin R. Swanson; Lisa A. Boardman; Hongzhe Sun; Junwen Wang

doi:10.1093/bioinformatics/btz123

MetaMarker: A pipeline for de novo discovery of novel metagenomic biomarkers

Mohamad Koohi-Moghadam, Mitesh J. Borad, Nhan L. Tran, Kristin R. Swanson, Lisa A. Boardman, Hongzhe Sun, Junwen Wang

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Summary: We present MetaMarker, a pipeline for discovering metagenomic biomarkers from whole-metagenome sequencing samples. Different from existing methods, MetaMarker is based on a de novo approach that does not require mapping raw reads to a reference database. We applied MetaMarker on whole-metagenome sequencing of colorectal cancer (CRC) stool samples from France to discover CRC specific metagenomic biomarkers. We showed robustness of the discovered biomarkers by validating in independent samples from Hong Kong, Austria, Germany and Denmark. We further demonstrated these biomarkers could be used to build a machine learning classifier for CRC prediction. Availability and implementation: MetaMarker is freely available at https://bitbucket.org/mkoohim/metamarker under GPLv3 license. Supplementary information: Supplementary data are available at Bioinformatics online.

Original language	English (US)
Pages (from-to)	3812-3814
Number of pages	3
Journal	Bioinformatics
Volume	35
Issue number	19
DOIs	https://doi.org/10.1093/bioinformatics/btz123
State	Published - Oct 1 2019

ASJC Scopus subject areas

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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10.1093/bioinformatics/btz123

Cite this

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abstract = "Summary: We present MetaMarker, a pipeline for discovering metagenomic biomarkers from whole-metagenome sequencing samples. Different from existing methods, MetaMarker is based on a de novo approach that does not require mapping raw reads to a reference database. We applied MetaMarker on whole-metagenome sequencing of colorectal cancer (CRC) stool samples from France to discover CRC specific metagenomic biomarkers. We showed robustness of the discovered biomarkers by validating in independent samples from Hong Kong, Austria, Germany and Denmark. We further demonstrated these biomarkers could be used to build a machine learning classifier for CRC prediction. Availability and implementation: MetaMarker is freely available at https://bitbucket.org/mkoohim/metamarker under GPLv3 license. Supplementary information: Supplementary data are available at Bioinformatics online.",

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AU - Borad, Mitesh J.

AU - Tran, Nhan L.

AU - Swanson, Kristin R.

AU - Boardman, Lisa A.

AU - Sun, Hongzhe

AU - Wang, Junwen

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MetaMarker: A pipeline for de novo discovery of novel metagenomic biomarkers

Abstract

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