Quantitative trait locus study design from an information perspective Journal Article


Authors: Sen, S.; Satagopan, J. M.; Churchill, G. A.
Article Title: Quantitative trait locus study design from an information perspective
Abstract: We examine the efficiency of different genotyping and phenotyping strategies in inbred line crosses from an information perspective. This provides a mathematical framework for the statistical aspects of QTL experimental design, while guiding our intuition. Our central result is a simple formula that quantifies the fraction of missing information of any genotyping strategy in a backcross. It includes the special case of selectively genotyping only the phenotypic extreme individuals. The formula is a function of the square of the phenotype and the uncertainty in our knowledge of the genotypes at a locus. This result is used to answer a variety of questions. First, we examine the cost-information trade-off varying the density of markers and the proportion of extreme phenotypic individuals genotyped. Then we evaluate the information content of selective phenotyping designs and the impact of measurement error in phenotyping. A simple formula quantifies the information content of any combined phenotyping and genotyping design. We extend our results to cover multigenotype crosses, such as the F2 intercross, and multiple QTL models. We find that when the QTL effect is small, any contrast in a multigenotype cross benefits from selective genotyping in the same manner as in a backcross. The benefit remains in the presence of a second unlinked QTL with small effect (explaining <20% of the variance), but diminishes if the second QTL has a large effect. Software for performing power calculations for backcross and F2 intercross incorporating selective genotyping and marker spacing is available from http:xywww.biostat.ucsf.edu/sen. Copyright © 2005 by the Genetics Society of America.
Keywords: review; research design; phenotype; animals; mice; genotype; gene mapping; statistical analysis; data interpretation, statistical; models, genetic; genome size; quantitative trait locus; quantitative trait loci; chromosome mapping; calculation; inbred strain; likelihood functions; quantitative trait locus mapping; maximum likelihood method; lod score
Journal Title: Genetics
Volume: 170
Issue: 1
ISSN: 0016-6731
Publisher: Genetics Society of America  
Date Published: 2005-05-01
Start Page: 447
End Page: 464
Language: English
DOI: 10.1534/genetics.104.038612
PUBMED: 15781700
PROVIDER: scopus
PMCID: PMC1449722
DOI/URL:
Notes: --- - "Cited By (since 1996): 19" - "Export Date: 24 October 2012" - "CODEN: GENTA" - "Source: Scopus"
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  1. Jaya M Satagopan
    141 Satagopan