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


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-10-01

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

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  • Journal

    TITLE

    Nature Methods

    ISSUE

    10

    VOLUME

    15

    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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