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dc.contributor.authorMurphy, Amy
dc.contributor.authorWeiss, Scott Tillman
dc.contributor.authorLange, Christoph
dc.date.accessioned2011-05-10T00:27:16Z
dc.date.issued2008
dc.identifier.citationMurphy, Amy, Scott T. Weiss, and Christoph Lange. 2008. Screening and Replication using the Same Data Set: Testing Strategies for Family-Based Studies in which All Probands Are Affected. PLoS Genetics 4(9): e1000197.en_US
dc.identifier.issn1553-7390en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:4885954
dc.description.abstractFor genome-wide association studies in family-based designs, we propose a powerful two-stage testing strategy that can be applied in situations in which parent-offspring trio data are available and all offspring are affected with the trait or disease under study. In the first step of the testing strategy, we construct estimators of genetic effect size in the completely ascertained sample of affected offspring and their parents that are statistically independent of the family-based association/transmission disequilibrium tests (FBATs/TDTs) that are calculated in the second step of the testing strategy. For each marker, the genetic effect is estimated (without requiring an estimate of the SNP allele frequency) and the conditional power of the corresponding FBAT/TDT is computed. Based on the power estimates, a weighted Bonferroni procedure assigns an individually adjusted significance level to each SNP. In the second stage, the SNPs are tested with the FBAT/TDT statistic at the individually adjusted significance levels. Using simulation studies for scenarios with up to 1,000,000 SNPs, varying allele frequencies and genetic effect sizes, the power of the strategy is compared with standard methodology (e.g., FBATs/TDTs with Bonferroni correction). In all considered situations, the proposed testing strategy demonstrates substantial power increases over the standard approach, even when the true genetic model is unknown and must be selected based on the conditional power estimates. The practical relevance of our methodology is illustrated by an application to a genome-wide association study for childhood asthma, in which we detect two markers meeting genome-wide significance that would not have been detected using standard methodology.en_US
dc.language.isoen_USen_US
dc.publisherPublic Library of Scienceen_US
dc.relation.isversionofdoi:10.1371/journal.pgen.1000197en_US
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC2529406/pdf/en_US
dash.licenseLAA
dc.subjectgenetics and genomicsen_US
dc.subjectcomplex traitsen_US
dc.subjectdisease modelsen_US
dc.subjectgenetics of diseaseen_US
dc.subjectmathematicsen_US
dc.subjectstatisticsen_US
dc.titleScreening and Replication using the Same Data Set: Testing Strategies for Family-Based Studies in which All Probands Are Affecteden_US
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden_US
dc.relation.journalPLoS Geneticsen_US
dash.depositing.authorWeiss, Scott Tillman
dc.date.available2011-05-10T00:27:16Z
dash.affiliation.otherHMS^Medicine-Brigham and Women's Hospitalen_US
dash.affiliation.otherSPH^Molecular+Integrative Physiological Sci Progen_US
dash.affiliation.otherHMS^Medicine-Brigham and Women's Hospitalen_US
dash.affiliation.otherSPH^Biostatisticsen_US
dc.identifier.doi10.1371/journal.pgen.1000197*
dash.contributor.affiliatedLange, Christoph
dash.contributor.affiliatedWeiss, Scott


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