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Bioinformatics. 2019 Mar 2. pii: btz123. doi: 10.1093/bioinformatics/btz123. [Epub ahead of print]

MetaMarker: a de novo pipeline for discovering novel metagenomic biomarkers.

Author information

1
Department of Health Sciences Research and Center for Individualized Medicine, Mayo Clinic, Scottsdale, AZ 85259, USA.
2
Department of Chemistry, The University of Hong Kong, Hong Kong SAR, P.R. China.
3
Center for Genomic Sciences, The University of Hong Kong, Hong Kong SAR, P.R. China.
4
Department of Hematology, Mayo Clinic, Scottsdale, AZ, USA.
5
Department of Cancer Biology, Mayo Clinic, Scottsdale, AZ, USA.
6
Department of Neurologic Surgery, Mayo Clinic, Scottsdale, AZ, USA.
7
Division of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA.
8
Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ, USA.

Abstract

SUMMARY:

We present MetaMarker, a pipeline for discovering metagenomic biomarkers from WMS 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 WMS 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 colorectal cancer 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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