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A Guide to QTL Mapping with R/qtlCase study I

A Guide to QTL Mapping with R/qtl: Case study I [In this chapter and the next, we present two case studies to illustrate the QTL mapping process in its entirety. We bring together tools from previous chapters and demonstrate their combined use to solve two moderately difficult problems. Both case studies have features that require special handling. In this sense they are not typical. On the other hand, almost every dataset has quirks that require an alert analyst to recognize them and respond accordingly. Our case studies illustrate the investigative process of QTL data analysis and improvisation using R/qtl.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Guide to QTL Mapping with R/qtlCase study I

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Publisher
Springer New York
Copyright
© Springer-Verlag New York 2009
ISBN
978-0-387-92124-2
Pages
283 –312
DOI
10.1007/978-0-387-92125-9_10
Publisher site
See Chapter on Publisher Site

Abstract

[In this chapter and the next, we present two case studies to illustrate the QTL mapping process in its entirety. We bring together tools from previous chapters and demonstrate their combined use to solve two moderately difficult problems. Both case studies have features that require special handling. In this sense they are not typical. On the other hand, almost every dataset has quirks that require an alert analyst to recognize them and respond accordingly. Our case studies illustrate the investigative process of QTL data analysis and improvisation using R/qtl.]

Published: Jun 5, 2009

Keywords: Multiple Imputation; Combine Data; Selective Genotyping; Initial Cross; Left Triangle

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