Adapting Random Forests to Predict Obesity-Associated Gene Expression.Random forests (RFs) are effective at predicting gene expression from genotype data. 
Random Forests
Our work shows that RFs compete with PrediXcan in the prediction of obesity-associated gene expression in subcutaneous adipose tissue, a highly relevant tissue to obesity.  Additionally, RFs generate predictions for obesity-associated genes where PrediXcan fails to do so.
PrediXcan