A critical assessment of gene catalogs for metagenomic analysis

Author:

Commichaux Seth123,Shah Nidhi14ORCID,Ghurye Jay14,Stoppel Alexander1,Goodheart Jessica A5,Luque Guillermo G6,Cummings Michael P1,Pop Mihai14ORCID

Affiliation:

1. Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, 20742, USA

2. Biological Science Graduate Program, University of Maryland, College Park, MD, 20742, USA

3. Division of Molecular Biology, Office of Applied Research and Safety Assessment, Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, Laurel, Maryland, 20708, USA

4. Department of Computer Science, University of Maryland, College Park, MD, 20742, USA

5. Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, 92037, USA

6. Department of Microbiome Science, Max Planck Institute for Developmental Biology, Tübingen, 72076, Germany

Abstract

Abstract Motivation Microbial gene catalogs are data structures that organize genes found in microbial communities, providing a reference for standardized analysis of the microbes across samples and studies. Although gene catalogs are commonly used, they have not been critically evaluated for their effectiveness as a basis for metagenomic analyses. Results As a case study, we investigate one such catalog, the Integrated Gene Catalog (IGC), however, our observations apply broadly to most gene catalogs constructed to date. We focus on both the approach used to construct this catalog and on its effectiveness when used as a reference for microbiome studies. Our results highlight important limitations of the approach used to construct the IGC and call into question the broad usefulness of gene catalogs more generally. We also recommend best practices for the construction and use of gene catalogs in microbiome studies and highlight opportunities for future research. Availability and implementation All supporting scripts for our analyses can be found on GitHub: https://github.com/SethCommichaux/IGC.git. The supporting data can be downloaded from: https://obj.umiacs.umd.edu/igc-analysis/IGC_analysis_data.tar.gz. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

Deutsche Forschungsgemeinschaft

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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