@Article{Uhl_Rabsch_Eggenhofer-Peakh_indiv_site-2022,
  author =	 {Uhl, Michael and Rabsch, Dominik and Eggenhofer, Florian 
                  and Backofen, Rolf},
  title =	 {Peakhood: individual site context extraction for {CLIP}-seq 
                  peak regions},
  journal =	 {Bioinformatics},
  year =	 {2022},
  volume =	 {38},
  number =	 {4},
  pages =	 {1139-1140},
  user =	 {backofen},
  pmid =	 {34734974},
  doi = 	 {10.1093/bioinformatics/btab755},
  issn = 	 {1367-4803},
  issn = 	 {1367-4811},
  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. 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. AVAILABILITY 
                  AND IMPLEMENTATION: Peakhood is freely available under MIT 
                  license at: https://github.com/BackofenLab/Peakhood. 
                  SUPPLEMENTARY INFORMATION: Supplementary data are available 
                  at Bioinformatics online.}
}