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• W2090249912 abstract "Abstract Background Existing software for quantitative trait mapping is either not able to model polygenic variation or does not allow incorporation of more than one genetic variance component. Improperly modeling the genetic relatedness among subjects can result in excessive false positives. We have developed an R package, QTLRel, to enable more flexible modeling of genetic relatedness as well as covariates and non-genetic variance components. Results We have successfully used the package to analyze many datasets, including F 34 body weight data that contains 688 individuals genotyped at 3105 SNP markers and identified 11 QTL. It took 295 seconds to estimate variance components and 70 seconds to perform the genome scan on an Linux machine equipped with a 2.40GHz Intel(R) Core(TM)2 Quad CPU. Conclusions QTLRel provides a toolkit for genome-wide association studies that is capable of calculating genetic incidence matrices from pedigrees, estimating variance components, performing genome scans, incorporating interactive covariates and genetic and non-genetic variance components, as well as other functionalities such as multiple-QTL mapping and genome-wide epistasis." @default.
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• W2090249912 date "2011-07-27" @default.
• W2090249912 modified "2023-10-18" @default.
• W2090249912 title "QTLRel: an R Package for Genome-wide Association Studies in which Relatedness is a Concern" @default.
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• W2090249912 doi "https://doi.org/10.1186/1471-2156-12-66" @default.
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