Quantitative trait loci (QTL) detection in multicross inbred designs

individual QTL genotypes under optimal QTL selection to maximize terminal response after ten generations for two unlinked (r = 0.5) or linked (r = 0.05) QTL with effects equal to

model (middle), and additive model (lower) when additive, dominance and epistasis e ffects are null (A); QTL II and QTL IV have additive effects without dominance and epistasis

Our study shows that cofactor analysis increased the number of false positives in all scenarios with low heritability and the increase was up to 50% in low power experiments and

Similarly for the joint tests developed for an F2 de- sign, the Type 1 error rates were inflated when there was segregation distortion (P = 0.7) and ET1 sampling (see Tab. II),

Selection in parental lines to increase power for QTL mapping Selection of high ranking individuals in one parental line and of low ranking individuals in another

Bayes factor / Quantitative Trait Loci / hypothesis testing / Markov Chain Monte

Efficiency of population structures for mapping of Mendelian and imprinted quantitative trait loci in outbred pigs using variance component methods...
INRA, EDP Sciences, 2005

Results: A quantitative trait locus (QTL) mapping approach involving two-step variance component analysis was employed using phenotypic data on 30852 palms from crosses between