PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of gseBioMed CentralBiomed Central Web Sitesearchsubmit a manuscriptregisterthis articleGenetics, Selection, Evolution : GSEJournal Front Page
 
Genet Sel Evol. 2004; 36(6): 601–619.
Published online Nov 15, 2004. doi:  10.1186/1297-9686-36-6-601
PMCID: PMC2697196
Joint tests for quantitative trait loci in experimental crosses
T Mark Beasley,corresponding author1 Dongyan Yang,1 Nengjun Yi,1 Daniel C Bullard,2 Elizabeth L Travis,3 Christopher I Amos,4 Shizhong Xu,5 and David B Allison1,6
1Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, AL, USA
2Department of Genomics and Pathobiology, University of Alabama at Birmingham, Birmingham, AL, USA
3Department of Experimental Radiation Oncology, University of Texas, M.D. Anderson Cancer Center, Houston, TX, USA
4Department of Epidemiology, University of Texas, M.D. Anderson Cancer Center Houston, TX, USA
5University of California, Riverside, CA, USA
6Clinical Nutrition Research Center, University of Alabama at Birmingham, Birmingham, AL, USA
corresponding authorCorresponding author.
T Mark Beasley: MBeasley/at/UAB.edu
Received February 16, 2004; Accepted May 24, 2004.
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 (i.e., 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 under both backcross and F2 intercross situations. Joint tests were generally more powerful for one-tailed selection under both backcross and F2 intercross situations. However, joint tests cannot be recommended for one-tailed selective genotyping if segregation distortion is suspected.
Keywords: joint tests, quantitative trait loci, linkage, F2 cross, backcross
 
(To access the full article, please see PDF)
Articles from Genetics, Selection, Evolution : GSE are provided here courtesy of
BioMed Central