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A Model-Based Approach to Identify Binding Sites in CLIP-Seq Data

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  • Tao Wang
  • Beibei Chen
  • MinSoo Kim
  • Yang Xie
  • Guanghua Xiao

Abstract

Cross-linking immunoprecipitation coupled with high-throughput sequencing (CLIP-Seq) has made it possible to identify the targeting sites of RNA-binding proteins in various cell culture systems and tissue types on a genome-wide scale. Here we present a novel model-based approach (MiClip) to identify high-confidence protein-RNA binding sites from CLIP-seq datasets. This approach assigns a probability score for each potential binding site to help prioritize subsequent validation experiments. The MiClip algorithm has been tested in both HITS-CLIP and PAR-CLIP datasets. In the HITS-CLIP dataset, the signal/noise ratios of miRNA seed motif enrichment produced by the MiClip approach are between 17% and 301% higher than those by the ad hoc method for the top 10 most enriched miRNAs. In the PAR-CLIP dataset, the MiClip approach can identify ∼50% more validated binding targets than the original ad hoc method and two recently published methods. To facilitate the application of the algorithm, we have released an R package, MiClip (http://cran.r-project.org/web/packages/MiClip/index.html), and a public web-based graphical user interface software (http://galaxy.qbrc.org/tool_runner?tool_id=mi_clip) for customized analysis.

Suggested Citation

  • Tao Wang & Beibei Chen & MinSoo Kim & Yang Xie & Guanghua Xiao, 2014. "A Model-Based Approach to Identify Binding Sites in CLIP-Seq Data," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-11, April.
  • Handle: RePEc:plo:pone00:0093248
    DOI: 10.1371/journal.pone.0093248
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    References listed on IDEAS

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    1. Donny D. Licatalosi & Aldo Mele & John J. Fak & Jernej Ule & Melis Kayikci & Sung Wook Chi & Tyson A. Clark & Anthony C. Schweitzer & John E. Blume & Xuning Wang & Jennifer C. Darnell & Robert B. Darn, 2008. "HITS-CLIP yields genome-wide insights into brain alternative RNA processing," Nature, Nature, vol. 456(7221), pages 464-469, November.
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