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Found 3 papers, 1 papers with code
rfPhen2Gen: A machine learning based association study of brain imaging phenotypes to genotypes
Moreover, random forests identified additional SNPs that were not prioritized by the linear models but are known to be associated with brain-related disorders.
High-dimensional multi-trait GWAS by reverse prediction of genotypes
Multi-trait genome-wide association studies (GWAS) use multi-variate statistical methods to identify associations between genetic variants and multiple correlated traits simultaneously, and have higher statistical power than independent univariate analyses of traits.
Restricted maximum-likelihood method for learning latent variance components in gene expression data with known and unknown confounders
Based on this result we propose a restricted maximum-likelihood method which estimates the latent variables by maximizing the likelihood on the restricted subspace orthogonal to the known confounding factors, and show that this reduces to probabilistic PCA on that subspace.
