Crunch: integrated processing and modeling of ChIP-seq data in terms of regulatory motifs

Berger, Severin and Pachkov, Mikhail and Arnold, Phil and Omidi, Saeed and Kelley, Nicholas and Salatino, Silvia and van Nimwegen, Erik. (2019) Crunch: integrated processing and modeling of ChIP-seq data in terms of regulatory motifs. Genome Research, 29 (7). pp. 1164-1177.

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Official URL: https://edoc.unibas.ch/71384/

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Although ChIP-seq has become a routine experimental approach for quantitatively characterizing the genome-wide binding of transcription factors (TFs), computational analysis procedures remain far from standardized, making it difficult to compare ChIP-seq results across experiments. In addition, although genome-wide binding patterns must ultimately be determined by local constellations of DNA-binding sites, current analysis is typically limited to identifying enriched motifs in ChIP-seq peaks. Here we present Crunch, a completely automated computational method that performs all ChIP-seq analysis from quality control through read mapping and peak detecting and that integrates comprehensive modeling of the ChIP signal in terms of known and novel binding motifs, quantifying the contribution of each motif and annotating which combinations of motifs explain each binding peak. By applying Crunch to 128 data sets from the ENCODE Project, we show that Crunch outperforms current peak finders and find that TFs naturally separate into "solitary TFs," for which a single motif explains the ChIP-peaks, and "cobinding TFs," for which multiple motifs co-occur within peaks. Moreover, for most data sets, the motifs that Crunch identified de novo outperform known motifs, and both the set of cobinding motifs and the top motif of solitary TFs are consistent across experiments and cell lines. Crunch is implemented as a web server, enabling standardized analysis of any collection of ChIP-seq data sets by simply uploading raw sequencing data. Results are provided both in a graphical web interface and as downloadable files.
Faculties and Departments:05 Faculty of Science > Departement Biozentrum > Computational & Systems Biology > Bioinformatics (van Nimwegen)
UniBasel Contributors:van Nimwegen, Erik and Berger, Severin and Pachkov, Mikhail and Omidi Klishami, Saeed and Kelley, Nicholas William and Salatino, Silvia
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Cold Spring Harbor Laboratory Press
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:17 Aug 2020 14:34
Deposited On:17 Aug 2020 14:34

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