Variance Components Linkage Analysis with Repeated Measurements
We extend the variance components approach to model repeated measures in a quantitative trait linkage study, which enables the evaluation of power and cost for different designs. Repeated measures substantially improve power and the proportional increase in LOD score depends mostly on measurement error and total heritability but not much on marker map or number of alleles per marker (i.e. relative insensitive to genotyping platforms). This website provids the R package to determine optimal number of repeated measures for given measurement error and cost. Two functions are provided:      BestRepeat(Vm, cost.pheno, Va, Vg, Ve, s) is used when parental phenotypes are available. (Instructions)      woparent.BestRepeat(Vm, cost.pheno, Va, Vg, Ve, s) is used when parental phenotypes are not available. (Instructions)
Registration form	If you use this program, please fill out the form.
Please email me: lianglim@umich.edu	Comments and suggestions are welcome!
BestRepeat_1.0.zip	R package for Windows
BestRepeat_1.0.tar.gz	R package for Linux
MERLIN tutorial	How to analyze your repeated measure data using MERLIN
Citation:	Liang L, Chen WM, Sham PC and Abecasis GR. (2008) Variance Components Linkage Analysis with Repeated Measurements. Human Heredity (in press)