How to analyze many contingency tables simultaneously in genetic association studies
Mostra el registre complet Registre parcial de l'ítem
- dc.contributor.author Dickhaus, Thorstenca
- dc.contributor.author Straßburger, Klausca
- dc.contributor.author Schunk, Danielca
- dc.contributor.author Morcillo Suárez, Carlos, 1969-ca
- dc.contributor.author Illig, Thomasca
- dc.contributor.author Navarro i Cuartiellas, Arcadi, 1969-ca
- dc.date.accessioned 2015-12-14T15:55:53Z
- dc.date.available 2015-12-14T15:55:53Z
- dc.date.issued 2012
- dc.description.abstract We study exact tests for (2 x 2) and (2 x 3) contingency tables, in particular exact chi-squared tests and exact tests of Fisher type. In practice, these tests are typically carried out without randomization, leading to reproducible results but not exhausting the significance level. We discuss that this can lead to methodological and practical issues in a multiple testing framework when many tables are simultaneously under consideration as in genetic association studies.Realized randomized p-values are proposed as a solution which is especially useful for data-adaptive (plug-in) procedures. These p-values allow to estimate the proportion of true null hypotheses much more accurately than their non-randomized counterparts. Moreover, we address the problem of positively correlated p-values for association by considering techniques to reduce multiplicity by estimating the "effective number of tests" from the correlation structure.An algorithm is provided that bundles all these aspects, efficient computer implementations are made available, a small-scale simulation study is presented and two real data examples are shown.ca
- dc.format.mimetype application/pdfca
- dc.identifier.citation Dickhaus T, Straßburger K, Schunk D, Morcillo-Suarez C, Illig T, Navarro A. How to analyze many contingency tables simultaneously in genetic association studies. Stat Appl Genet Mol Biol. 2012;11(4):12. DOI: 10.1515/1544-6115.1776ca
- dc.identifier.doi http://dx.doi.org/10.1515/1544-6115.1776
- dc.identifier.issn 1544-6115
- dc.identifier.uri http://hdl.handle.net/10230/25427
- dc.language.iso engca
- dc.publisher De Gruyterca
- dc.relation.ispartof Statistical applications in genetics and molecular biology. 2012;11(4):12
- dc.rights © De Gruyter Published version available at http://www.degruyter.com/view/j/sagmb.2012.11.issue-4/1544-6115.1776/1544-6115.1776.xml http://dx.doi.org/10.1515/1544-6115.1776ca
- dc.rights.accessRights info:eu-repo/semantics/openAccessca
- dc.subject.keyword Contingency tables
- dc.subject.keyword Effective number of tests
- dc.subject.keyword Genome-wide association study
- dc.subject.keyword Multiplicity correction
- dc.subject.keyword Realized randomized p-values
- dc.subject.keyword Validation stage
- dc.subject.other Biologia computacional -- Mètodesca
- dc.title How to analyze many contingency tables simultaneously in genetic association studiesca
- dc.type info:eu-repo/semantics/articleca
- dc.type.version info:eu-repo/semantics/publishedVersionca