Local epigenomic state cannot discriminate interacting and non-interacting enhancer-promoter pairs with high accuracy.

ABSTRACT: We report an experimental design issue in recent machine learning formulations of the enhancer-promoter interaction problem arising from the fact that many enhancer-promoter pairs share features. Cross-fold validation schemes which do not correctly separate these feature sharing enhancer-promoter pairs into one test set report high accuracy, which is actually arising from high training set accuracy and a failure to properly evaluate generalization performance. Cross-fold validation schemes which properly segregate pairs with shared features show markedly reduced ability to predict enhancer-promoter interactions from epigenomic state. Parameter scans with multiple models indicate that local epigenomic features of individual pairs of enhancers and promoters cannot distinguish those pairs tha

SUBMITTER: Xi W 

PROVIDER: S-EPMC6298642 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature