Handling highly correlated genes in prediction analysis of genomic studies. (arXiv:2007.02455v4 [stat.AP] UPDATED)

Background: Selecting feature genes to predict phenotypes is one of the
typical tasks in analyzing genomics data. Though many general-purpose
algorithms were developed for prediction, dealing with highly correlated genes
in the prediction model is still not well addressed. High correlation among
genes introduces technical problems, such as multi-collinearity issues, leading
to unreliable prediction models. Furthermore, when a causal gene (whose
variants have an actual biological effect on a phenotype) is highly correlated
with other genes, most algorithms select the …

analysis arxiv genes prediction studies