QTL mapping in a mixed model framework with separate detection and localization stages. The former detects the number of QTL on each chromosome based on the genetic variation due to the grouped markers on the chromosome, while the latter stage uses this information to determine the most likely QTL positions. The mixed model can accommodate general fixed and random effects, including spatial effects in field trials and random pedigree effects.
dlcross is a constructor function for
objects to be input to
It will read in files in several different formats, including the qtl
cross format and two new formats to
accommodate association mapping populations and designs with extensive
The primary function is
dlmap, which performs the iterative
algorithm to detect and position QTL on all chromosomes with significant
genetic variation. This can accomodate sophisticated mixed models for phenotypic
variation in addition to the genetic modeling.
Because ASReml-R is proprietary, we provide the option of using the nlme package to fit mixed models via the
algorithm argument. However, there
are some features which are only accessible when the
algorithm used is
The vignette included in this package gives more background on the methodology, input file structure, and examples of how to use each of the important functions in the package.
Emma Huang and Andrew George
Maintainer: Emma Huang <Emma.Huang@csiro.au>
Huang, B.E. and George, A.W. 2009. Look before you leap: A new approach to QTL mapping. TAG 119:899-911
B. Emma Huang, Rohan Shah, Andrew W. George (2012). dlmap: An R Package for Mixed Model QTL and Association Analysis. Journal of Statistical Software 50(6): 1-22. URL http://www.jstatsoft.org/v50/i06/.
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