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Claus-Dieter Mayer

dblp:19/7432 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2009
0000-0001-8788-3149ORCID · reported

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

Applied, interdisciplinary, general and emerging computing · 1

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 · 81% Computational science and engineering · 19%

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › gene expression analysis › gene expression meta-analysis
microarray meta-analysis
0.112009
Moderated effect size and P-value combinations for microarray meta-analyses · Bioinform. 2009
Bioinformatics and computational biology › gene expression analysis
differential expression analysis
0.012009
Moderated effect size and P-value combinations for microarray meta-analyses · Bioinform. 2009
Computational science and engineering › statistical significance testing
p-value combination
0.012009
Moderated effect size and P-value combinations for microarray meta-analyses · Bioinform. 2009

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

simulation study · 0.1moderated effect size · 0.1meta-analysis · 0.1
YearPublicationVenuePosition
2009 Moderated effect size and P-value combinations for microarray meta-analyses
abstract
MOTIVATION: With the proliferation of microarray experiments and their availability in the public domain, the use of meta-analysis methods to combine results from different studies increases. In microarray experiments, where the sample size is often limited, meta-analysis offers the possibility to considerably increase the statistical power and give more accurate results. RESULTS: A moderated effect size combination method was proposed and compared with other meta-analysis approaches. All methods were applied to real publicly available datasets on prostate cancer, and were compared in an extensive simulation study for various amounts of inter-study variability. Although the proposed moderated effect size combination improved already existing effect size approaches, the P-value combination was found to provide a better sensitivity and a better gene ranking than the other meta-analysis methods, while effect size methods were more conservative. AVAILABILITY: An R package metaMA is available on the CRAN.
Guillemette Marot, Jean-Louis Foulley, Claus-Dieter Mayer, Florence Jaffrézic
Bioinform.3