Delta.EPI: a probabilistic voting-based enhancer-promoter interaction prediction platform

Enhancer promoter interaction (EPI) involves most of gene transcriptional regulation in the high eukaryotes. Predicting the EPIs from given genomic loci or DNA sequences is not a trivial task. The benchmarking work so far for EPI predictors is more or less empirical and lacks quantitative model-based comparisons, posing challenges for molecular biologists to obtain reliable EPI predictions. Here, we present an EPI prediction platform, namely Delta.EPI. Based on a statistic model of the data integration, Delta.EPI is capable of comprehensively assessing the predictions from four state-of-the-art EPI predictors. Equipped with a user-friendly interface and visualization platform, Delta.EPI presents the sorted results with the confidence of EPI relevance, which may guide the molecular biologists who lack the pre-knowledge of the algorithms of EPI prediction. Last, we showcase the utility of Delta.EPI with a case study. Delta.EPI provides a powerful tool to fuel the gene regulation and 3D genome studies by ease-to-access EPI predictions. Delta.EPI can be freely accessed at https://ngdc.cncb.ac.cn/deltaEPI/.Copyright & COPY; 2023, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Limited and Science Press. All rights reserved.