Qiita: rapid, web-enabled microbiome meta-analysis

By Antonio Gonzalez, Jose A Navas-Molina, T. Kościółek, Daniel McDonald, Yoshiki Vazquez-Baeza, Gail L Ackermann, J. Dereus, Stefan Janssen, Austin D. Swafford, Stephanie B. Orchanian and 13 more. Nature Methods, 2018

578 citations recorded by the source corpus.

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. The Qiita web platform provides access to large amounts of public microbial multi-omic data and enables easy analysis and meta-analysis of standardized private and public data.

Subfields: Molecular Biology, Physiology

View Paper: https://www.semanticscholar.org/paper/c88aeb8b633082be61d8c27633549079bca70ee3

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Citations in the corpus

QIIME 2 Enables Comprehensive End‐to‐End Analysis of Diverse Microbiome Data and Comparative Studies with Publicly Available Data (2020, methodology): “This produces a long output, as there are several sequencing technologies, sequence trim lengths, a few different variable regions, and multiple feature assessment methods represented.”
A practical guide to amplicon and metagenomic analysis of microbiome data (2020, methodology): “For users who are not familiar with command lines, webservers such as Qiita (Gonzalez et al., 2018), MGnify (Mitchell et al., 2020), and gcMeta (Shi et al., 2019b) could be used to perform analysis.”