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William D. Shannon

dblp:75/9581 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2016
0000-0002-7386-8949ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › microbiology
microbiome study design
0.212016
A web application for sample size and power calculation in case-control microbiome studies · Bioinform. 2016
Bioinformatics and computational biology › biostatistics
sample size determination
0.212016
A web application for sample size and power calculation in case-control microbiome studies · Bioinform. 2016
Bioinformatics and computational biology
statistical genetics
0.112016
A web application for sample size and power calculation in case-control microbiome studies · Bioinform. 2016

Methods — techniques the papers use, named apart from their topics

wilcoxon-mann-whitney test · 0.2generalized wald test · 0.2dirichlet-multinomial model · 0.2
YearPublicationVenuePosition
2016 A web application for sample size and power calculation in case-control microbiome studies
abstract
UNLABELLED: : When designing a case-control study to investigate differences in microbial composition, it is fundamental to assess the sample sizes needed to detect an hypothesized difference with sufficient statistical power. Our application includes power calculation for (i) a recoded version of the two-sample generalized Wald test of the 'HMP' R-package for comparing community composition, and (ii) the Wilcoxon-Mann-Whitney test for comparing operational taxonomic unit-specific abundances between two samples (optional). The simulation-based power calculations make use of the Dirichlet-Multinomial model to describe and generate abundances. The web interface allows for easy specification of sample and effect sizes. As an illustration of our application, we compared the statistical power of the two tests, with and without stratification of samples. We observed that statistical power increases considerably when stratification is employed, meaning that less samples are needed to detect the same effect size with the same power. AVAILABILITY AND IMPLEMENTATION: The web interface is written in R code using Shiny (RStudio Inc., 2016) and it is available at https://fedematt.shinyapps.io/shinyMB The R code for the recoded generalized Wald test can be found at https://github.com/mafed/msWaldHMP CONTACT: [email protected].
Federico Mattiello, Bie M. P. Verbist, Karoline Faust, Jeroen Raes, William D. Shannon, Luc Bijnens, Olivier Thas
Bioinform.5
2006 Improving Adherence to Coronary Heart Disease Secondary Prevention Medication Guidelines at a Community Hospital
Thomas C. Bailey, Laura A. Noirot, Brian F. Gage, William D. Shannon, Brian Waterman, Stuti Sinha, Dennis A. Bouselli, Richard M. Reichley, Anne C. Goldberg, W. Claiborne Dunagan
AMIA5