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A Pipeline for PAR-CLIP Data Analysis.

Marvin Jens1

  • 1Systems Biology of Gene Regulatory Elements, Max-Delbrück-Centrum für Molekulare Medizin, Berlin, Germany. marvin.jens@mdc-berlin.de.

Methods in Molecular Biology (Clifton, N.J.)
|October 15, 2015
PubMed
Summary

This study details computational methods for analyzing photo-activatable ribonucleoside cross-linking and immunoprecipitation (PAR-CLIP) sequencing data to identify RNA-binding protein (RBP) binding sites. It provides a step-by-step guide to process, align, and cluster reads, minimizing false positives for accurate RBP-binding site detection.

Keywords:
Adapter removalBWABWA PSSMBinding siteCLIPConsensus-binding sitesCross-linkingFLEXBARFalse-positive filteringHigh-throughputNext-generation sequencingPAR-CLIPRBPRNARNA-binding proteinRead mappingSmall RNATranscriptomeUVmRNAmiRNA

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Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • Photo-activatable ribonucleoside cross-linking and immunoprecipitation (PAR-CLIP) is crucial for mapping RNA-binding protein (RBP) interactions across the transcriptome.
  • Understanding RBP binding sites is essential for deciphering gene regulation and RNA processing.
  • Computational analysis of PAR-CLIP data presents challenges due to UV-induced mutations and potential mapping artifacts.

Purpose of the Study:

  • To provide a comprehensive computational workflow for analyzing PAR-CLIP sequencing data.
  • To explain the specific challenges in PAR-CLIP data analysis, including read mutation and mapping artifacts.
  • To guide researchers in accurately identifying RBP-binding sites using open-source tools.

Main Methods:

  • Pre-processing and alignment of high-throughput sequencing reads generated from PAR-CLIP experiments.
  • Aggregation of aligned reads into clusters representing putative RBP-binding sites.
  • Implementation of strategies like mapping decoys and adaptive quality filtering to control for false positives.

Main Results:

  • A detailed, step-by-step procedure for the computational analysis of PAR-CLIP data is presented.
  • Methods are described to account for UV-induced mutations in sequencing reads.
  • Techniques for artifact control are outlined to enhance the accuracy of RBP-binding site identification.

Conclusions:

  • The presented computational framework enables robust and accurate identification of RBP-binding sites from PAR-CLIP data.
  • The use of open-source tools ensures accessibility and reproducibility of the analysis.
  • This workflow contributes to a deeper understanding of RNA-binding protein functions in gene regulation.