Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A Guide to QTL Mapping with R/qtlWorking with covariates

A Guide to QTL Mapping with R/qtl: Working with covariates [It is often of interest to take account of a covariate (such as sex or an environmental factor, such as diet) in QTL mapping. If such a covariate has a large effect on the phenotype, its inclusion in the analysis will result in reduced residual variation and so will enhance our ability to detect QTL. It is also of interest to assess possible QTL × covariate interactions. For example, does a QTL have different effects in the two sexes?] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Guide to QTL Mapping with R/qtlWorking with covariates

Download PDF
33 pages

Loading next page...
 
/lp/springer-journals/a-guide-to-qtl-mapping-with-r-qtl-working-with-covariates-YLPkOrY65L
Publisher
Springer New York
Copyright
© Springer-Verlag New York 2009
ISBN
978-0-387-92124-2
Pages
179 –211
DOI
10.1007/978-0-387-92125-9_7
Publisher site
See Chapter on Publisher Site

Abstract

[It is often of interest to take account of a covariate (such as sex or an environmental factor, such as diet) in QTL mapping. If such a covariate has a large effect on the phenotype, its inclusion in the analysis will result in reduced residual variation and so will enhance our ability to detect QTL. It is also of interest to assess possible QTL × covariate interactions. For example, does a QTL have different effects in the two sexes?]

Published: Jun 5, 2009

Keywords: Additive Covariates; Marker Covariates; Hyper Data; Binary Phenotype; Miss Genotype Data

There are no references for this article.