| Literature DB >> 28967885 |
Rashmi Sinha1, Galeb Abu-Ali2,3, Emily Vogtmann1, Anthony A Fodor4, Boyu Ren2, Amnon Amir5, Emma Schwager2,3, Jonathan Crabtree6, Siyuan Ma2,3, Christian C Abnet1, Rob Knight5,7, Owen White6, Curtis Huttenhower2,3.
Abstract
In order for human microbiome studies to translate into actionable outcomes for health, meta-analysis of reproducible data from population-scale cohorts is needed. Achieving sufficient reproducibility in microbiome research has proven challenging. We report a baseline investigation of variability in taxonomic profiling for the Microbiome Quality Control (MBQC) project baseline study (MBQC-base). Blinded specimen sets from human stool, chemostats, and artificial microbial communities were sequenced by 15 laboratories and analyzed using nine bioinformatics protocols. Variability depended most on biospecimen type and origin, followed by DNA extraction, sample handling environment, and bioinformatics. Analysis of artificial community specimens revealed differences in extraction efficiency and bioinformatic classification. These results may guide researchers in experimental design choices for gut microbiome studies.Entities:
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Year: 2017 PMID: 28967885 PMCID: PMC5839636 DOI: 10.1038/nbt.3981
Source DB: PubMed Journal: Nat Biotechnol ISSN: 1087-0156 Impact factor: 54.908