Title |
Hypothesis Testing and Power Calculations for Taxonomic-Based Human Microbiome Data
|
---|---|
Published in |
PLOS ONE, December 2012
|
DOI | 10.1371/journal.pone.0052078 |
Pubmed ID | |
Authors |
Patricio S. La Rosa, J. Paul Brooks, Elena Deych, Edward L. Boone, David J. Edwards, Qin Wang, Erica Sodergren, George Weinstock, William D. Shannon |
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 non-parametric 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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 6 | 27% |
Australia | 4 | 18% |
United Kingdom | 3 | 14% |
Germany | 2 | 9% |
India | 1 | 5% |
Canada | 1 | 5% |
Egypt | 1 | 5% |
Sweden | 1 | 5% |
Unknown | 3 | 14% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 13 | 59% |
Members of the public | 8 | 36% |
Practitioners (doctors, other healthcare professionals) | 1 | 5% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 17 | 3% |
Canada | 3 | <1% |
Argentina | 2 | <1% |
Germany | 2 | <1% |
India | 2 | <1% |
United Kingdom | 2 | <1% |
Netherlands | 1 | <1% |
Sweden | 1 | <1% |
Portugal | 1 | <1% |
Other | 4 | <1% |
Unknown | 622 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 163 | 25% |
Student > Ph. D. Student | 135 | 21% |
Student > Master | 63 | 10% |
Professor > Associate Professor | 43 | 7% |
Student > Doctoral Student | 40 | 6% |
Other | 111 | 17% |
Unknown | 102 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 211 | 32% |
Biochemistry, Genetics and Molecular Biology | 89 | 14% |
Medicine and Dentistry | 89 | 14% |
Immunology and Microbiology | 33 | 5% |
Mathematics | 27 | 4% |
Other | 82 | 12% |
Unknown | 126 | 19% |