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

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.

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 Creators:
Ramisch, Anna1, Author
Heinrich, Verena1, Author
Glaser, Laura V.1, Author
Fuchs, Alisa1, Author
Yang, Xinyi1, Author
Benner, Philipp1, Author
Schöpflin, Robert1, Author
Li, Na1, Author
Kinkley, Sarah1, Author
Römer-Hillmann, Anja1, Author
Longinotto, John2, Author
Heyne, Steffen2, Author
Czepukojc, Beate1, Author
Kessler, Sonja M.1, Author
Kiemer, Alexandra K.1, Author
Cadenas, Cristina1, Author
Arrigoni, Laura2, Author
Gasparoni, Nina1, Author
Manke, Thomas2, Author           
Pap, Thomas1, Author
Pospisilik, Andrew2, Author           Hengstler, Jan1, AuthorWalter, Jörn1, AuthorMeijsing, Sebastiaan H.1, Author Chung, Ho-Ryun1, AuthorVingron, Martin1, Author more..
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1External Organizations, ou_persistent22              
2Max Planck Institute of Immunobiology and Epigenetics, Max Planck Society, ou_2243644              

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Free keywords: Enhancer predition, Enhancer dynamics, Gene regulation, Epigenetics, Random forest, Differential analysis, Histone modification, 3D interaction
 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.

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Language(s): eng - English
 Dates: 2019
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1186/s13059-019-1860-7
 Degree: -

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Title: Genome Biology : Biology for the Post-Genomic Era
Source Genre: Journal
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Publ. Info: London : BioMed Central Ltd.
Pages: - Volume / Issue: 20 Sequence Number: - Start / End Page: 227 Identifier: ISSN: 1465-6906
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000224390