redbiom: a Rapid Sample Discovery and Feature Characterization System
Date
2019-06-25
Authors
McDonald, Daniel
Kaehler, Benjamin
Gonzalez, Antonio
DeReus, Jeff
Ackermann, Gail
Marotz, Clarisse
Huttley, Gavin
Knight, Rob
Journal Title
Journal ISSN
Volume Title
Publisher
American Society for Microbiology
Abstract
Meta-analyses at the whole-community level have been important in microbiome studies, revealing profound features that structure Earth’s microbial communities, such as the unique differentiation of microbes from the mammalian gut relative to free-living microbial communities, the separation of microbiomes in saline and nonsaline environments, and the role of pH in driving soil microbial compositions. However, our ability to identify the specific features of a microbiome that differentiate these community-level patterns have lagged behind, especially as ever-cheaper DNA sequencing has yielded increasingly large data sets. One critical gap is the ability to search for samples that contain specific features (for example, sub-operational taxonomic units [sOTUs] identified by high-resolution statistical methods for removing amplicon sequencing errors). Here we introduce redbiom, a microbiome caching layer, which allows users to rapidly query samples that contain a given feature, retrieve sample data and metadata, and search for samples that match specified metadata values or ranges (e.g., all samples with a pH of >7), implemented using an in-memory NoSQL database called Redis. By default, redbiom allows public anonymous sample access for over 100,000 publicly available samples in the Qiita database. At over 100,000 samples, the caching server requires only 35 GB of resident memory. We highlight how redbiom enables a new type of characterization of microbiome samples and provide tutorials for using redbiom with QIIME 2. redbiom is open source under the BSD license, hosted on GitHub, and can be deployed independently of Qiita to enable search of proprietary or clinically restricted microbiome databases.
Description
Keywords
database, meta-analysis, microbiome
Citation
McDonald D, Kaehler B, Gonzalez A, DeReus J, Ackermann G, Marotz C, Huttley G, Knight R. 2019. redbiom: a rapid sample discovery and feature characterization system. mSystems 4:e00215-19. https://doi.org/10 .1128/mSystems.00215-19.
Collections
Source
mSystems
Type
Journal article
Book Title
Entity type
Access Statement
Open Access
License Rights
Creative Commons Attribution 4.0 International license
DOI
10.1128/mSystems.00215-19