Qiita: rapid, web-enabled microbiome meta-analysis View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-10

AUTHORS

Antonio Gonzalez, Jose A. Navas-Molina, Tomasz Kosciolek, Daniel McDonald, Yoshiki Vázquez-Baeza, Gail Ackermann, Jeff DeReus, Stefan Janssen, Austin D. Swafford, Stephanie B. Orchanian, Jon G. Sanders, Joshua Shorenstein, Hannes Holste, Semar Petrus, Adam Robbins-Pianka, Colin J. Brislawn, Mingxun Wang, Jai Ram Rideout, Evan Bolyen, Matthew Dillon, J. Gregory Caporaso, Pieter C. Dorrestein, Rob Knight

ABSTRACT

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. More... »

PAGES

796-798

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41592-018-0141-9

DOI

http://dx.doi.org/10.1038/s41592-018-0141-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1107129414

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30275573


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Download the RDF metadata as:  json-ld nt turtle xml License info

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RDF/XML is a standard XML format for linked data.

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