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- Title
Hypothesis Testing and Power Calculations for Taxonomic-Based Human Microbiome Data.
- Authors
Rosa, Patricio S. La; Brooks, J. Paul; Deych, Elena; Boone, Edward L.; Edwards, David J.; Wang, Qin; Sodergren, Erica; Weinstock, George; Shannon, William D.
- Abstract
This paper presents new biostatistical methods for the analysis of microbiome data based on a fully parametric approach using all the data. The Dirichlet-multinomial distribution allows the analyst to calculate power and sample sizes for experimental design, perform tests of hypotheses (e.g., compare microbiomes across groups), and to estimate parameters describing microbiome properties. The use of a fully parametric model for these data has the benefit over alternative nonparametric approaches such as bootstrapping and permutation testing, in that this model is able to retain more information contained in the data. This paper details the statistical approaches for several tests of hypothesis and power/sample size calculations, and applies them for illustration to taxonomic abundance distribution and rank abundance distribution data using HMP Jumpstart data on 24 subjects for saliva, subgingival, and supragingival samples. Software for running these analyses is available.
- Publication
PLoS ONE, 2012, Vol 7, Issue 12, p1
- ISSN
1932-6203
- Publication type
Academic Journal
- DOI
10.1371/journal.pone.0052078