AUTHOR=Hu Bin , Canon Shane , Eloe-Fadrosh Emiley A. , Anubhav , Babinski Michal , Corilo Yuri , Davenport Karen , Duncan William D. , Fagnan Kjiersten , Flynn Mark , Foster Brian , Hays David , Huntemann Marcel , Jackson Elais K. Player , Kelliher Julia , Li Po-E. , Lo Chien-Chi , Mans Douglas , McCue Lee Ann , Mouncey Nigel , Mungall Christopher J. , Piehowski Paul D. , Purvine Samuel O. , Smith Montana , Varghese Neha Jacob , Winston Donald , Xu Yan , Chain Patrick S. G. TITLE=Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale JOURNAL=Frontiers in Bioinformatics VOLUME=1 YEAR=2022 URL=https://www.frontiersin.org/journals/bioinformatics/articles/10.3389/fbinf.2021.826370 DOI=10.3389/fbinf.2021.826370 ISSN=2673-7647 ABSTRACT=

The nascent field of microbiome science is transitioning from a descriptive approach of cataloging taxa and functions present in an environment to applying multi-omics methods to investigate microbiome dynamics and function. A large number of new tools and algorithms have been designed and used for very specific purposes on samples collected by individual investigators or groups. While these developments have been quite instructive, the ability to compare microbiome data generated by many groups of researchers is impeded by the lack of standardized application of bioinformatics methods. Additionally, there are few examples of broad bioinformatics workflows that can process metagenome, metatranscriptome, metaproteome and metabolomic data at scale, and no central hub that allows processing, or provides varied omics data that are findable, accessible, interoperable and reusable (FAIR). Here, we review some of the challenges that exist in analyzing omics data within the microbiome research sphere, and provide context on how the National Microbiome Data Collaborative has adopted a standardized and open access approach to address such challenges.