Nutrigenomic Study
Study the effects of five diet treatments on 21 liver lipids and 120 hepatic gene expression in wild-type and PPAR-alpha deficient mice. We use a multivariate mixed random forest analysis by regressing gene expression, diet and genotype (the x-variables) on lipid expressions (the multivariate y-responses).
Martin P.G. et al. (2007). Novel aspects of PPAR-alpha-mediated regulation of lipid and xenobiotic metabolism revealed through a nutrigenomic study. Hepatology, 45(3), 767–777.
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## multivariate mixed forests
## lipids used as the multivariate y
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## load the data
data(nutrigenomic, package = "randomForestSRC")
## multivariate mixed forest call
mv.obj <- rfsrc(get.mv.formula(colnames(nutrigenomic$lipids)),
data.frame(do.call(cbind, nutrigenomic)),
importance=TRUE, nsplit = 10)
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## plot the standarized performance and VIMP values
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## acquire the error rate for each of the 21-coordinates
## standardize to allow for comparison across coordinates
serr <- get.mv.error(mv.obj, standardize = TRUE)
## acquire standardized VIMP
svimp <- get.mv.vimp(mv.obj, standardize = TRUE)
par(mfrow = c(1,2))
plot(serr, xlab = "Lipids", ylab = "Standardized Performance")
matplot(svimp, xlab = "Genes/Diet/Genotype", ylab = "Standardized VIMP")
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## plot some trees
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plot(get.tree(mv.obj, 1))
plot(get.tree(mv.obj, 2))
plot(get.tree(mv.obj, 3))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.