Hostname: page-component-76fb5796d-skm99 Total loading time: 0 Render date: 2024-04-26T02:37:21.302Z Has data issue: false hasContentIssue false

Application of non-parametric bootstrap methods to estimate confidence intervals for QTL location in a beef cattle QTL experimental population

Published online by Cambridge University Press:  02 August 2002

JONGJOO KIM
Affiliation:
Animal Science Department, Texas A&M University, College Station, TX 78743, USA
SCOTT K. DAVIS
Affiliation:
Animal Science Department, Texas A&M University, College Station, TX 78743, USA
JEREMY F. TAYLOR
Affiliation:
Animal Science Department, Texas A&M University, College Station, TX 78743, USA
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Empirical confidence intervals (CIs) for the estimated quantitative trait locus (QTL) location from selective and non-selective non-parametric bootstrap resampling methods were compared for a genome scan involving an Angus×Brahman reciprocal fullsib backcross population. Genetic maps, based on 357 microsatellite markers, were constructed for 29 chromosomes using CRI-MAP V2.4. Twelve growth, carcass composition and beef quality traits (n = 527–602) were analysed to detect QTLs utilizing (composite) interval mapping approaches. CIs were investigated for 28 likelihood ratio test statistic (LRT) profiles for the one QTL per chromosome model. The CIs from the non-selective bootstrap method were largest (87·7 cM average or 79·2% coverage of test chromosomes). The Selective II procedure produced the smallest CI size (42·3 cM average). However, CI sizes from the Selective II procedure were more variable than those produced by the two LOD drop method. CI ranges from the Selective II procedure were also asymmetrical (relative to the most likely QTL position) due to the bias caused by the tendency for the estimated QTL position to be at a marker position in the bootstrap samples and due to monotonicity and asymmetry of the LRT curve in the original sample.

Type
Research Article
Copyright
© 2002 Cambridge University Press