Fit and exploration of multiple-QTL models

Part of the Statistics for Biology and Health book series (SBH)

The majority of efforts for QTL mapping have used a hypothesis testing approach. For example, in single-QTL analyses (Chap. 4), one considers each genomic position, one at a time, and asks the question, “Is there a QTL here?” A primary focus is on the adjustment for the number of tests (i.e., for the scan across the genome), to control the rate of false positive declarations of linkage.


Pairwise Interaction Extraneous Locus Multiple Interval Mapping Hyper 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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

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

Personalised recommendations