A model-based approach to identify binding sites in CLIP-seq data

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

Research output: Contribution to journalArticle

17 Citations (Scopus)

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.

Original languageEnglish (US)
Article numbere93248
JournalPLoS One
Volume9
Issue number4
DOIs
StatePublished - Apr 8 2014

Fingerprint

MicroRNAs
binding sites
Binding Sites
Galaxies
RNA-Binding Proteins
Graphical user interfaces
RNA
Cell culture
Seed
user interface
RNA-binding proteins
Genes
Throughput
Tissue
Proteins
microRNA
crosslinking
cell culture
methodology
Immunoprecipitation

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

A model-based approach to identify binding sites in CLIP-seq data. / Wang, Tao; Chen, Beibei; Kim, MinSoo; Xie, Yang; Xiao, Guanghua.

In: PLoS One, Vol. 9, No. 4, e93248, 08.04.2014.

Research output: Contribution to journalArticle

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