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Center for Bioinformatics & Molecular Biostatistics
University of California, San Francisco

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R/qtlDesign: Inbred Line Cross Experimental Design
Saunak Sen, University of California, San Francisco
Jaya Satagopan, Memorial Sloan-Kettering Cancer Center
Karl W. Broman, The Johns Hopkins Bloomberg School of Public Health
Gary A. Churchill, The Jackson Laboratory

Download the Paper (194 K, PDF file) - November 1, 2006 Tell a colleague about it.
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ABSTRACT:
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.

SUGGESTED CITATION:
Saunak Sen, Jaya Satagopan, Karl W. Broman, and Gary A. Churchill, "R/qtlDesign: Inbred Line Cross Experimental Design" (November 1, 2006). Center for Bioinformatics & Molecular Biostatistics. Paper qtl-powercalculations.
http://repositories.cdlib.org/cbmb/qtl-powercalculations

 
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