Qiita: rapid, web-enabled microbiome meta-analysis.,Nature Methods

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Qiita: rapid, web-enabled microbiome meta-analysis.
Nature Methods ( IF 36.1 ) Pub Date : 2018-10-01 , DOI: 10.1038/s41592-018-0141-9
Antonio Gonzalez ₁ , Jose A Navas-Molina _{1,

2,

3} , Tomasz Kosciolek ₁ , Daniel McDonald ₁ , Yoshiki Vázquez-Baeza ₁ , Gail Ackermann ₁ , Jeff DeReus ₁ , Stefan Janssen ₁ , Austin D Swafford ₄ , Stephanie B Orchanian ₄ , Jon G Sanders ₁ , Joshua Shorenstein _{1,

5} , Hannes Holste _{1,

2} , Semar Petrus ₆ , Adam Robbins-Pianka ₇ , Colin J Brislawn ₈ , Mingxun Wang ₉ , Jai Ram Rideout ₁₀ , Evan Bolyen ₁₀ , Matthew Dillon ₁₀ , J Gregory Caporaso _{10,

11} , Pieter C Dorrestein _{1,

4,

9} , Rob Knight _{1,

2,

4}

Affiliation

Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA.
Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA.
Google LLC, Mountain View, CA, USA.
Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA.
Inscripta, Inc., Boulder, CO, USA.
Department of Biology, University of California, San Diego, La Jolla, CA, USA.
Department of Computer Science, University of Colorado, Boulder, Boulder, CO, USA.
Earth & Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, USA.
Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA.
Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ, USA.
Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA.

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.

中文翻译：

Qiita：快速、支持网络的微生物组元分析。

对微生物组功能和组成的多组学见解通常一次推进一项研究。然而，为了充分理解研究之间的关系，必须将数据汇总到荟萃分析中。这使得通过查找跨生物样本和数据层可重现的特征来生成新假设成为可能。Qiita 在基于 Web 的微生物组比较平台中显着加速了此类集成任务，我们通过人类微生物组项目和综合人类微生物组项目 (iHMP) 数据进行了演示。

更新日期：2018-12-10

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