학술논문
CRUP: a comprehensive framework to predict condition-specific regulatory units
Document Type
Original Paper
Author
Ramisch, Anna; Heinrich, Verena; Glaser, Laura V.; Fuchs, Alisa; Yang, Xinyi; Benner, Philipp; Schöpflin, Robert; Li, Na; Kinkley, Sarah; Römer-Hillmann, Anja; Longinotto, John; Heyne, Steffen; Czepukojc, Beate; Kessler, Sonja M.; Kiemer, Alexandra K.; Cadenas, Cristina; Arrigoni, Laura; Gasparoni, Nina; Manke, Thomas; Pap, Thomas; Pospisilik, John A.; Hengstler, Jan; Walter, Jörn; Meijsing, Sebastiaan H.; Chung, Ho-Ryun; Vingron, Martin
Source
Genome Biology. 20(1)
Subject
Language
English
ISSN
1474-760X
Abstract
We present the software Condition-specific Regulatory Units Prediction (CRUP) to infer from epigenetic marks a list of regulatory units consisting of dynamically changing enhancers with their target genes. The workflow consists of a novel pre-trained enhancer predictor that can be reliably applied across cell types and species, solely based on histone modification ChIP-seq data. Enhancers are subsequently assigned to different conditions and correlated with gene expression to derive regulatory units. We thoroughly test and then apply CRUP to a rheumatoid arthritis model, identifying enhancer-gene pairs comprising known disease genes as well as new candidate genes.