R/qtlDesign: inbred line cross experimental design

R/qtlDesign: inbred line cross experimental design 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 . http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Mammalian Genome Springer Journals

R/qtlDesign: inbred line cross experimental design

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Publisher
Springer Journals
Copyright
Copyright © 2007 by Springer Science+Business Media, Inc.
Subject
Life Sciences; Cell Biology; Anatomy; Zoology
ISSN
0938-8990
eISSN
1432-1777
D.O.I.
10.1007/s00335-006-0090-y
Publisher site
See Article on Publisher Site

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 .

Journal

Mammalian GenomeSpringer Journals

Published: Mar 8, 2007

References

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