This is a first version of the EMRF program that incorporates the EM-based Haseman-Elston regression (Kruglyak et al., 1996, Am J of Hum Genet 58:1347-1363) and the random forest by Breiman (2001, Machine Learning, 45, 5-32) and provides various measures of importance on each marker as described in

Lee SSF. Random Forests for Multi-Locus Quantitative Trait Linkage Analysis. PhD Thesis, University of Toronto, 2007.

Lee SSF, Sun L, Kustra R, and Bull SB. EM-random forest and new measures of variable importance for multi-locus quantitative trait linkage analysis. Bioinformatics 2008 24(14):1603-1610.

Supplementary Information

Any questions/comments or suggestions that you may have for improving the programs or documentation can be sent to sophia[at]utstat[dot]utoronto[dot]ca.

README
Overview
GNU GENERAL PUBLIC LICENSE

1) For data at individual or genotype level (i.e. Genotype data and quantitative trait values)

Input
Output
Example
Download EMRF.IndivLevel

2) For data at the IBD level (i.e. IBD data and squared difference in sib-pair trait values)

Input
Output
Example
Download EMRF.IBDLevel