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Journal Article

CRUP: a comprehensive framework to predict condition-specific regulatory units

MPS-Authors

Longinotto,  John
Max Planck Institute of Immunobiology and Epigenetics, Max Planck Society;

Heyne,  Steffen
Max Planck Institute of Immunobiology and Epigenetics, Max Planck Society;

Arrigoni,  Laura
Max Planck Institute of Immunobiology and Epigenetics, Max Planck Society;

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Manke,  Thomas
Max Planck Institute of Immunobiology and Epigenetics, Max Planck Society;

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Pospisilik,  Andrew
Max Planck Institute of Immunobiology and Epigenetics, Max Planck Society;

External Resource

https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1860-7
(Publisher version)

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Citation

Ramisch, A., Heinrich, V., Glaser, L. V., Fuchs, A., Yang, X., Benner, P., et al. (2019). CRUP: a comprehensive framework to predict condition-specific regulatory units. Genome Biology: Biology for the Post-Genomic Era, 20, 227. doi:10.1186/s13059-019-1860-7.


Cite as: https://hdl.handle.net/21.11116/0000-0005-1C56-C
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.