The Genboree Microbiome Toolset and the analysis of 16S rRNA microbial sequences

Microbial metagenomic analyses rely on an increasing number of publicly available tools. Installation, integration, and maintenance of the tools poses significant burden on many researchers and creates a barrier to adoption of microbiome analysis, particularly in translational settings. To address t...

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Bibliographic Details
Published in:BMC bioinformatics 2012, Vol.13 Suppl 13 (Suppl 13), p.S11-S11, Article S11
Main Authors: Riehle, Kevin, Coarfa, Cristian, Jackson, Andrew, Ma, Jun, Tandon, Arpit, Paithankar, Sameer, Raghuraman, Sriram, Mistretta, Toni-Ann, Saulnier, Delphine, Raza, Sabeen, Diaz, Maria Alejandra, Shulman, Robert, Aagaard, Kjersti, Versalovic, James, Milosavljevic, Aleksandar
Format: Article
Language:English
Subjects:
Access control
Adoption
Application programming interface
Bioinformatics
Biotechnology
Child
Children
Classification
Cloud computing
Computational Biology
Data processing
Digestive tract
Gastrointestinal Tract - microbiology
Humans
Integration
Irritable bowel syndrome
Irritable Bowel Syndrome - microbiology
Learning algorithms
Medicine
Metadata
Metagenome
Metagenomics - methods
Microbiology
Obesity
Obesity - genetics
Phylogenetics
Phylogeny
R&D
Research & development
RNA, Ribosomal, 16S - genetics
rRNA 16S
Sequence Analysis, RNA - methods
Software
Software services
Taxonomy
Translation
Twins
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Summary:Microbial metagenomic analyses rely on an increasing number of publicly available tools. Installation, integration, and maintenance of the tools poses significant burden on many researchers and creates a barrier to adoption of microbiome analysis, particularly in translational settings. To address this need we have integrated a rich collection of microbiome analysis tools into the Genboree Microbiome Toolset and exposed them to the scientific community using the Software-as-a-Service model via the Genboree Workbench. The Genboree Microbiome Toolset provides an interactive environment for users at all bioinformatic experience levels in which to conduct microbiome analysis. The Toolset drives hypothesis generation by providing a wide range of analyses including alpha diversity and beta diversity, phylogenetic profiling, supervised machine learning, and feature selection. We validate the Toolset in two studies of the gut microbiota, one involving obese and lean twins, and the other involving children suffering from the irritable bowel syndrome. By lowering the barrier to performing a comprehensive set of microbiome analyses, the Toolset empowers investigators to translate high-volume sequencing data into valuable biomedical discoveries.
ISSN:1471-2105
1471-2105
DOI:10.1186/1471-2105-13-S13-S11