Measuring the microbiome: Best practices for developing and benchmarking microbiomics methods

Nicholas A Bokulich; Michal Ziemski; Michael S Robeson 2nd; Benjamin D Kaehler

doi:10.1016/j.csbj.2020.11.049

Measuring the microbiome: Best practices for developing and benchmarking microbiomics methods

Comput Struct Biotechnol J. 2020 Dec 3:18:4048-4062. doi: 10.1016/j.csbj.2020.11.049. eCollection 2020.

Authors

Nicholas A Bokulich¹, Michal Ziemski¹, Michael S Robeson 2nd², Benjamin D Kaehler³

Affiliations

¹ Laboratory of Food Systems Biotechnology, Institute of Food, Nutrition, and Health, ETH Zurich, Switzerland.
² University of Arkansas for Medical Sciences, Department of Biomedical Informatics, Little Rock, AR, USA.
³ School of Science, University of New South Wales, Canberra, Australia.

Abstract

Microbiomes are integral components of diverse ecosystems, and increasingly recognized for their roles in the health of humans, animals, plants, and other hosts. Given their complexity (both in composition and function), the effective study of microbiomes (microbiomics) relies on the development, optimization, and validation of computational methods for analyzing microbial datasets, such as from marker-gene (e.g., 16S rRNA gene) and metagenome data. This review describes best practices for benchmarking and implementing computational methods (and software) for studying microbiomes, with particular focus on unique characteristics of microbiomes and microbiomics data that should be taken into account when designing and testing microbiomics methods.

Keywords: Amplicon sequencing; Benchmarking; Best practices; Marker-gene sequencing; Metagenomics; Microbiome; Software development.

Publication types

Review