R/qtlDesign: inbred line cross experimental design
- 218 Downloads
An investigator planning a QTL (quantitative trait locus) experiment has to choose which strains to cross, the type of cross, genotyping strategies, and the number of progeny to raise and phenotype. To help make such choices, we have developed an interactive program for power and sample size calculations for QTL experiments, R/qtlDesign. Our software includes support for selective genotyping strategies, variable marker spacing, and tools to optimize information content subject to cost constraints for backcross, intercross, and recombinant inbred lines from two parental strains. We review the impact of experimental design choices on the variance attributable to a segregating locus, the residual error variance, and the effective sample size. We give examples of software usage in real-life settings. The software is available at http://www.biostat.ucsf.edu/sen/software.html.
KeywordsQuantitative Trait Locus Recombinant Inbred Line Effective Sample Size Quantitative Trait Locus Effect Quantitative Trait Locus Detection
The authors thank two anonymous reviewers for helpful comments on this article and the software. They thank Cynthia Piontkowski for editorial assistance. Their work was supported by NIH grants GM060457 (JMS), GM074244 (KWB), and GM070683 (GAC).
- Broman KW (2001) Review of statistical methods for QTL mapping in experimental crosses. Lab Anim 30(7), 44–52Google Scholar
- Cox D, Hinkley D (1974) Theoretical Statistics Chapman and Hall: LondonGoogle Scholar
- Kearsey M, Pooni HS (1996) The Genetical Analysis of Quantitative Traits Chapman and Hall: LondonGoogle Scholar
- Lynch M, Walsh B (1998) Genetics and analysis of quantitative traits Sinauer Associates Inc.: Sunderland, MAGoogle Scholar
- Rapp JP (2000) Genetic analysis of inherited hypertension in the rat. Physiol Rev 80, 131–172Google Scholar
- Silver LM (1995) Mouse genetics Oxford University Press: OxfordGoogle Scholar