A simple linear regression method for quantitative trait loci linkage analysis with censored observations

Anderson, Carl A., McRae, Allan F. and Visscher, Peter M. (2006) A simple linear regression method for quantitative trait loci linkage analysis with censored observations. Genetics, 173 3: 1735-1745. doi:10.1534/genetics.106.055921


Author Anderson, Carl A.
McRae, Allan F.
Visscher, Peter M.
Title A simple linear regression method for quantitative trait loci linkage analysis with censored observations
Journal name Genetics   Check publisher's open access policy
ISSN 0016-6731
Publication date 2006-07-01
Year available 2006
Sub-type Article (original research)
DOI 10.1534/genetics.106.055921
Open Access Status Not yet assessed
Volume 173
Issue 3
Start page 1735
End page 1745
Total pages 11
Place of publication BETHESDA
Publisher GENETICS SOCIETY AMERICA
Language eng
Abstract Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.
Keyword Maximum-Likelihood
Dairy-Cattle
Muscle Mass
Igf2 Locus
Qtl
Survival
Maps
Genomics
Models
Gene
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Unknown

Document type: Journal Article
Sub-type: Article (original research)
Collection: WoS Import - Archived
 
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Created: Mon, 13 Nov 2017, 08:02:43 EST