Single-QTL analysis

  • Karl W. Broman
  • Śaunak Sen
Part of the Statistics for Biology and Health book series (SBH)

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.


Marker Regression Multiple Imputation Approach Hyper Data Miss Genotype Data Marker Genotype Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag New York 2009

Authors and Affiliations

  1. 1.Dept. Biostatistics & Medical InformaticsUniversity of Wisconsin-MadisonMadisonUSA
  2. 2.Dept. Epidemiology & BiostatisticsUniversity of California San FranciscoSan FranciscoUSA

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