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Titolo: Incorporation of covariates in multipoint modelfree linkage analysis of binary traits: how important are unaffecteds?
Autore: Alcais, A; Abel, L;
 Indirizzi:
 INSERM, U550, Necker Med Sch, Lab Human Genet Infect Dis, F75015 Paris, France INSERM Paris France F75015 uman Genet Infect Dis, F75015 Paris, France
 Titolo Testata:
 EUROPEAN JOURNAL OF HUMAN GENETICS
fascicolo: 8,
volume: 9,
anno: 2001,
pagine: 613  620
 SICI:
 10184813(200108)9:8<613:IOCIMM>2.0.ZU;2N
 Fonte:
 ISI
 Lingua:
 ENG
 Soggetto:
 SIBPAIR ANALYSIS; QUANTITATIVE TRAITS; ALCOHOL DEPENDENCE; GENETICLINKAGE; SIBSHIPS; SUSCEPTIBILITY; SEGREGATION; ROBUSTNESS; LOCI;
 Keywords:
 covariates; unaffected; linkage analysis; MaximumLikelihoodBinomial; logistic residuals; mixed model;
 Tipo documento:
 Article
 Natura:
 Periodico
 Settore Disciplinare:
 Life Sciences
 Citazioni:
 32
 Recensione:
 Indirizzi per estratti:
 Indirizzo: Alcais, A INSERM, U550, Necker Med Sch, Lab Human Genet Infect Dis, F75015 Paris, France INSERM Paris France F75015 Infect Dis, F75015 Paris, France



 Citazione:
 A. Alcais e L. Abel, "Incorporation of covariates in multipoint modelfree linkage analysis of binary traits: how important are unaffecteds?", EUR J HUM G, 9(8), 2001, pp. 613620
Abstract
When the mode of inheritance is unknown, genetic linkage analysis of binary trait is commonly performed using affectedsibpair approaches. When there is evidence that some covariates influence the phenotype, incorporation of this information is expected to increase the power of the analysis since it allows (1) a better specification of the phenotype and (2) to take into account unaffected subjects. Here, we show how to account for covariates inthe sibshiporiented MaximumLikelihoodBinomial (MLB) linkage method by means of Pearson's logistic regression residuals which are computed using phenotypic and covariate information on both affected and unaffected subjects. These residuals are subsequently analysed as a quantitative phenotype with the corresponding extension of the MLB approach which can be used withoutany assumption on the distribution of these residuals. Then, a large simulation study is performed to study the relative power of incorporating or not unaffected sibs. To this aim, two different strategies in the multipoint analysis of family data are compared: (1) using residuals of the whole sibships (ie both covariate and genotypic information on unaffecteds is needed), and (2) using affecteds only (no information on unaffecteds is needed), under different generating models according to genetic and covariate effects. The results show that there is a clear increment in the power to detect the susceptibility locus when making use of the information carried by unaffecteds, in particular for dominant mode of inheritance and when values of the covariates influencing the disease are shared by all the members of the family.
ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 08/04/20 alle ore 11:44:42