title: BackCLIP: a tool to identify common background presence in PAR-CLIP datasets.
abstract: BACKGROUND
  PAR-CLIP, a CLIP-seq protocol, derives a transcriptome wide set of binding sites for RNA-binding proteins. Even though the protocol uses stringent washing to remove experimental noise, some of it remains. A recent study measured three sets of non-specific RNA backgrounds which are present in several PAR-CLIP datasets. However, a tool to identify the presence of common background in PAR-CLIP datasets is not yet available.
  
  
  RESULTS
  We used the measured sets of non-specific RNA backgrounds to build a common background set. Each element from the common background set has a score that reflects its presence in several PAR-CLIP datasets. We present a tool that uses this score to identify the amount of common backgrounds present in a PAR-CLIP dataset, and we provide the user the option to use or remove it. We used the proposed strategy in 30 PAR-CLIP datasets from nine proteins. It is possible to identify the presence of common backgrounds in a dataset and identify differences in datasets for the same protein. This method is the first step in the process of completely removing such backgrounds.
  
  
  BACKGROUND
  The tool was implemented in python. The common background set and the supplementary data are available at https://github.com/phrh/BackCLIP.
  
  
  BACKGROUND
  phreyes@gmail.com
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Colombian Corporation for Agricultural Research (CORPOICA), 250047 Bogotá, Colombia.
authors.forename: P H
authors.initials: PH
authors.lastname: Reyes-Herrera
authors.affiliation: Universidad Antonio Nariño, 110311 Bogotá, Colombia.
authors.forename: C A
authors.initials: CA
authors.lastname: Speck-Hernandez
authors.affiliation: Universidad Antonio Nariño, 110311 Bogotá, Colombia.
authors.forename: C A
authors.initials: CA
authors.lastname: Sierra
authors.affiliation: Woods Hole Oceanographic Institution, 02543 Massachusetts, USA and Massachusetts Institute of Technology, 02139 Massachusetts, USA.
authors.forename: S
authors.initials: S
authors.lastname: Herrera
mesh_terms: D003432:Cross-Linking Reagents / Q000737:chemistry*; D030541:Databases, Genetic; D047468:Immunoprecipitation / Q000379:methods*; D016601:RNA-Binding Proteins / Q000378:metabolism; D012984:Software; D014466:Ultraviolet Rays
chemical_list: D003432:Cross-Linking Reagents; D016601:RNA-Binding Proteins