Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học thế giới đề tài: Joint tests for quantitative trait loci in experimental crosses | Genet. Sel. Evol. 36 2004 601-619 601 INRA EDP Sciences 2004 DOI gse 2004020 Original article Joint tests for quantitative trait loci in experimental crosses T. Mark BEASLEYa Dongyan YANGa Nengjun Yla Daniel C. BưLLARDb Elizabeth L. Travisc Christopher I. AMOSd Shizhong Xue David B. ALLISONa f a Department of Biostatistics Section on Statistical Genetics University of Alabama at Birmingham Birmingham AL USA b Department of Genomics and Pathobiology University of Alabama at Birmingham Birmingham AL USA c Department of Experimental Radiation Oncology University of Texas . Anderson Cancer Center Houston TX USA d Department of Epidemiology University of Texas . Anderson Cancer Center Houston TX USA e University of California Riverside CA USA f Clinical Nutrition Research Center University of Alabama at Birmingham Birmingham AL USA Received 16 February 2004 accepted 24 May 2004 Abstract - Selective genotyping is common because it can increase the expected correlation between QTL genotype and phenotype and thus increase the statistical power of linkage tests . regression-based tests . Linkage can also be tested by assessing whether the marginal genotypic distribution conforms to its expectation a marginal-based test. We developed a class of joint tests that by constraining intercepts in regression-based analyses capitalize on the information available in both regression-based and marginal-based tests. We simulated data corresponding to the null hypothesis of no QTL effect and the alternative of some QTL effect at the locus for a backcross and an F2 intercross between inbred strains. Regression-based and marginal-based tests were compared to corresponding joint tests. We studied the effects of random sampling selective sampling from a single tail of the phenotypic distribution and selective sampling from both tails of the phenotypic distribution. Joint tests were nearly as powerful as all competing alternatives for random sampling and two-tailed selection
