1. Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale
- Author
-
Bin Hu, Shane Canon, Emiley A. Eloe-Fadrosh, null Anubhav, Michal Babinski, Yuri Corilo, Karen Davenport, William D. Duncan, Kjiersten Fagnan, Mark Flynn, Brian Foster, David Hays, Marcel Huntemann, Elais K. Player Jackson, Julia Kelliher, Po-E. Li, Chien-Chi Lo, Douglas Mans, Lee Ann McCue, Nigel Mouncey, Christopher J. Mungall, Paul D. Piehowski, Samuel O. Purvine, Montana Smith, Neha Jacob Varghese, Donald Winston, Yan Xu, and Patrick S. G. Chain
- Subjects
Computer applications to medicine. Medical informatics ,Human Genome ,R858-859.7 ,Genetics ,microbiome ,bioinformatics ,Generic health relevance ,infrastructure ,microbial ecology ,omics - 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.
- Published
- 2021