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Qiita: rapid, web-enabled microbiome meta-analysis
- Gonzalez, Antonio;
- Navas-Molina, Jose A;
- Kosciolek, Tomasz;
- McDonald, Daniel;
- Vázquez-Baeza, Yoshiki;
- Ackermann, Gail;
- DeReus, Jeff;
- Janssen, Stefan;
- Swafford, Austin D;
- Orchanian, Stephanie B;
- Sanders, Jon G;
- Shorenstein, Joshua;
- Holste, Hannes;
- Petrus, Semar;
- Robbins-Pianka, Adam;
- Brislawn, Colin J;
- Wang, Mingxun;
- Rideout, Jai Ram;
- Bolyen, Evan;
- Dillon, Matthew;
- Caporaso, J Gregory;
- Dorrestein, Pieter C;
- Knight, Rob
Published Web Location
https://doi.org/10.1038/s41592-018-0141-9Abstract
Multi-omic insights into microbiome function and composition typically advance one study at a time. However, in order for relationships across studies to be fully understood, data must be aggregated into meta-analyses. This makes it possible to generate new hypotheses by finding features that are reproducible across biospecimens and data layers. Qiita dramatically accelerates such integration tasks in a web-based microbiome-comparison platform, which we demonstrate with Human Microbiome Project and Integrative Human Microbiome Project (iHMP) data.
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