The most commonly used method for QTL analysis is interval mapping, in which one posits the presence of a single QTL and considers each point on a dense grid across the genome, one at a time, as the location of the putative QTL. A central issue concerns the treatment of missing genotype information: at a position between genetic markers, genotype data are not available and must be inferred on the basis of the available marker genotype data. Several methods are available; we describe the most popular. These methods all have analogs for the fit of multiple-QTL models, which will be discussed in Chap.8 and 9. We further discuss the establishment of statistical significance in such single-QTL genome scans, and the special treatment that is required for the X chromosome. But first, in order to introduce the basic ideas in QTL mapping, we describe an even simpler method, sometimes called marker regression.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2009 Springer-Verlag New York
About this chapter
Cite this chapter
Broman, K.W., Sen, Ĺš. (2009). Single-QTL analysis. In: A Guide to QTL Mapping with R/qtl. Statistics for Biology and Health. Springer, New York, NY. https://doi.org/10.1007/978-0-387-92125-9_4
Download citation
DOI: https://doi.org/10.1007/978-0-387-92125-9_4
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-92124-2
Online ISBN: 978-0-387-92125-9
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)