Literature DB >> 33792639

A critical assessment of gene catalogs for metagenomic analysis.

Seth Commichaux1,2,3, Nidhi Shah1,4, Jay Ghurye1,4, Alexander Stoppel1, Jessica A Goodheart5, Guillermo G Luque6, Michael P Cummings1, Mihai Pop1,4.   

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: 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.
© The Author(s) 2021. Published by Oxford University Press.

Entities:  

Year:  2021        PMID: 33792639     DOI: 10.1093/bioinformatics/btab216

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  2 in total

Review 1.  Inferring microbiota functions from taxonomic genes: a review.

Authors:  Christophe Djemiel; Pierre-Alain Maron; Sébastien Terrat; Samuel Dequiedt; Aurélien Cottin; Lionel Ranjard
Journal:  Gigascience       Date:  2022-01-12       Impact factor: 6.524

2.  Measuring quality of DNA sequence data via degradation.

Authors:  Alan F Karr; Jason Hauzel; Adam A Porter; Marcel Schaefer
Journal:  PLoS One       Date:  2022-08-03       Impact factor: 3.752

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.