Analysis of composition of microbiomes: a novel method for studying microbial composition

Microbial Ecology in Health and Disease

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Title Analysis of composition of microbiomes: a novel method for studying microbial composition
 
Creator Mandal, Siddhartha; Norwegian Institute of Public Health
Van Treuren, Will; Stanford University
White, Richard A; Norwegian Institute of Public Health
Eggesbø, Merete; Norwegian Institute of Public Health
Knight, Rob; University of California, San Diego
Peddada, Shyamal D.; National Institute of Environmental Health Sciences
 
Subject Analysis of microbiome data; Microbiome composition; Relative Abundance; Logratio
 
Description Background: Understanding the factors regulating our microbiota is important but requires appropriate statistical methodology. When comparing two or more populations most existing approaches either discount the underlying compositional structure in the microbiome data or use probability models such as the multinomial and Dirichlet-multinomial distributions, which may impose a correlation structure not suitable for microbiome data.Objective: To develop a methodology that accounts for compositional constraints to reduce false discoveries in detecting differentially abundant taxa at an ecosystem level, while maintaining high statistical power.Methods: We introduced a novel statistical framework called analysis of composition of microbiomes (ANCOM). ANCOM accounts for the underlying structure in the data and can be used for comparing the composition of microbiomes in two or more populations. ANCOM makes no distributional assumptions and can be implemented in a linear model framework to adjust for covariates as well as model longitudinal data. ANCOM also scales well to compare samples involving thousands of taxa.Results: We compared the performance of ANCOM to the standard t-test and a recently published methodology called Zero Inflated Gaussian (ZIG) methodology (1) for drawing inferences on the mean taxa abundance in two or more populations. ANCOM controlled the false discovery rate (FDR) at the desired nominal level while also improving power, whereas the t-test and ZIG had inflated FDRs, in some instances as high as 68% for the t-test and 60% for ZIG. We illustrate the performance of ANCOM using two publicly available microbial datasets in the human gut, demonstrating its general applicability to testing hypotheses about compositional differences in microbial communities.Conclusion: Accounting for compositionality using log-ratio analysis results in significantly improved inference in microbiota survey data.Keywords: constrained; relative abundance; log-ratio(Published: 29 May 2015)Citation: Microbial Ecology in Health & Disease 2015, 26: 27663 - http://dx.doi.org/10.3402/mehd.v26.27663To access the supplementary material for this article, please see Supplementary files under ‘Article Tools’
 
Publisher Microbial Ecology in Health and Disease
 
Contributor Intramural Research Program of the NIH National Institute of Environmental Health Sciences [Z01 ES101744-04]
Norwegian Research Council [214324]
Howard Hughes Medical Institute Early Career Scientist
 
Date 2015-05-29
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

 
Format application/pdf
text/html
application/epub+zip
application/xml
 
Identifier http://www.microbecolhealthdis.net/index.php/mehd/article/view/27663
10.3402/mehd.v26.27663
 
Source Microbial Ecology in Health and Disease; Vol 26 (2015)
1651-2235
 
Language eng
 
Relation http://www.microbecolhealthdis.net/index.php/mehd/article/view/27663/40390
http://www.microbecolhealthdis.net/index.php/mehd/article/view/27663/40391
http://www.microbecolhealthdis.net/index.php/mehd/article/view/27663/40392
http://www.microbecolhealthdis.net/index.php/mehd/article/view/27663/40393
http://www.microbecolhealthdis.net/index.php/mehd/article/downloadSuppFile/27663/19270
http://www.microbecolhealthdis.net/index.php/mehd/article/downloadSuppFile/27663/19271
http://www.microbecolhealthdis.net/index.php/mehd/article/downloadSuppFile/27663/19272
http://www.microbecolhealthdis.net/index.php/mehd/article/downloadSuppFile/27663/20510
http://www.microbecolhealthdis.net/index.php/mehd/article/downloadSuppFile/27663/20511
http://www.microbecolhealthdis.net/index.php/mehd/article/downloadSuppFile/27663/20685
http://www.microbecolhealthdis.net/index.php/mehd/article/downloadSuppFile/27663/20686
http://www.microbecolhealthdis.net/index.php/mehd/article/downloadSuppFile/27663/20687
http://www.microbecolhealthdis.net/index.php/mehd/article/downloadSuppFile/27663/20733
http://www.microbecolhealthdis.net/index.php/mehd/article/downloadSuppFile/27663/21050
 
Rights Copyright (c) 2015 Microbial Ecology in Health and Disease
http://creativecommons.org/licenses/by-nc/4.0
 

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