Welcome to the UPF Digital Repository

How to analyze many contingency tables simultaneously in genetic association studies

Show simple item record

dc.contributor.author Dickhaus, Thorsten
dc.contributor.author Straßburger, Klaus
dc.contributor.author Schunk, Daniel
dc.contributor.author Morcillo Suárez, Carlos, 1969-
dc.contributor.author Illig, Thomas
dc.contributor.author Navarro i Cuartiellas, Arcadi, 1969-
dc.date.accessioned 2015-12-14T15:55:53Z
dc.date.available 2015-12-14T15:55:53Z
dc.date.issued 2012
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: 10.1515/1544-6115.1776
dc.identifier.issn 1544-6115
dc.identifier.uri http://hdl.handle.net/10230/25427
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.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher De Gruyter
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/10.1515/1544-6115.1776
dc.subject.other Biologia computacional -- Mètodes
dc.title How to analyze many contingency tables simultaneously in genetic association studies
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1515/1544-6115.1776
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.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse

My Account

Statistics

In collaboration with Compliant to Partaking