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Peakhood: individual site context extraction for CLIP-seq peak regions.

Authors :
Uhl M
Rabsch D
Eggenhofer F
Backofen R
Source :
Bioinformatics (Oxford, England) [Bioinformatics] 2022 Jan 27; Vol. 38 (4), pp. 1139-1140.
Publication Year :
2022

Abstract

Motivation: CLIP-seq is by far the most widely used method to determine transcriptome-wide binding sites of RNA-binding proteins (RBPs). The binding site locations are identified from CLIP-seq read data by tools termed peak callers. Many RBPs bind to a spliced RNA (i.e. transcript) context, but all currently available peak callers only consider and report the genomic context. To accurately model protein binding behavior, a tool is needed for the individual context assignment to CLIP-seq peak regions.<br />Results: Here we present Peakhood, the first tool that utilizes CLIP-seq peak regions identified by peak callers, in tandem with CLIP-seq read information and genomic annotations, to determine which context applies, individually for each peak region. For sites assigned to transcript context, it further determines the most likely splice variant, and merges results for any number of datasets to obtain a comprehensive collection of transcript context binding sites.<br />Availability and Implementation: Peakhood is freely available under MIT license at: https://github.com/BackofenLab/Peakhood.<br />Supplementary Information: Supplementary data are available at Bioinformatics online.<br /> (© The Author(s) 2021. Published by Oxford University Press.)

Details

Language :
English
ISSN :
1367-4811
Volume :
38
Issue :
4
Database :
MEDLINE
Journal :
Bioinformatics (Oxford, England)
Publication Type :
Academic Journal
Accession number :
34734974
Full Text :
https://doi.org/10.1093/bioinformatics/btab755