微生物群
计算机科学
Web应用程序
数据科学
计算生物学
基因组
万维网
生物
生物信息学
遗传学
基因
作者
Antonio González,José A. Navas-Molina,Tomasz Kościółek,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 Brislawn,Mingxun Wang,Jai Ram Rideout,Evan Bolyen,Matthew R. Dillon
出处
期刊:Nature Methods
[Nature Portfolio]
日期:2018-09-20
卷期号:15 (10): 796-798
被引量:579
标识
DOI:10.1038/s41592-018-0141-9
摘要
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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