Site identification in high-throughput RNA-protein interaction data

Philip J. Uren, Emad Bahrami-Samani, Suzanne C. Burns, Mei Qiao, Fedor V. Karginov, Emily Hodges, Gregory J. Hannon, Jeremy R. Sanford, Luiz O Penalva, Andrew D. Smith

Research output: Contribution to journalArticle

123 Citations (Scopus)

Abstract

Motivation: Post-transcriptional and co-transcriptional regulation is a crucial link between genotype and phenotype. The central players are the RNA-binding proteins, and experimental technologies [such as cross-linking with immunoprecipitation-(CLIP-) and RIP-seq] for probing their activities have advanced rapidly over the course of the past decade. Statistically robust, flexible computational methods for binding site identification from high-throughput immunoprecipitation assays are largely lacking however.Results: We introduce a method for site identification which provides four key advantages over previous methods: (i) it can be applied on all variations of CLIP and RIP-seq technologies, (ii) it accurately models the underlying read-count distributions, (iii) it allows external covariates, such as transcript abundance (which we demonstrate is highly correlated with read count) to inform the site identification process and (iv) it allows for direct comparison of site usage across cell types or conditions.

Original languageEnglish (US)
Pages (from-to)3013-3020
Number of pages8
JournalBioinformatics
Volume28
Issue number23
DOIs
StatePublished - Dec 2012

Fingerprint

RNA
High Throughput
Throughput
Proteins
Protein
Immunoprecipitation
RNA-Binding Proteins
Count
Binding sites
Computational methods
Interaction
Technology
Assays
Transcriptional Regulation
Binding Sites
Genotype
Phenotype
Computational Methods
Linking
Covariates

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computational Mathematics
  • Statistics and Probability
  • Medicine(all)

Cite this

Uren, P. J., Bahrami-Samani, E., Burns, S. C., Qiao, M., Karginov, F. V., Hodges, E., ... Smith, A. D. (2012). Site identification in high-throughput RNA-protein interaction data. Bioinformatics, 28(23), 3013-3020. https://doi.org/10.1093/bioinformatics/bts569

Site identification in high-throughput RNA-protein interaction data. / Uren, Philip J.; Bahrami-Samani, Emad; Burns, Suzanne C.; Qiao, Mei; Karginov, Fedor V.; Hodges, Emily; Hannon, Gregory J.; Sanford, Jeremy R.; Penalva, Luiz O; Smith, Andrew D.

In: Bioinformatics, Vol. 28, No. 23, 12.2012, p. 3013-3020.

Research output: Contribution to journalArticle

Uren, PJ, Bahrami-Samani, E, Burns, SC, Qiao, M, Karginov, FV, Hodges, E, Hannon, GJ, Sanford, JR, Penalva, LO & Smith, AD 2012, 'Site identification in high-throughput RNA-protein interaction data', Bioinformatics, vol. 28, no. 23, pp. 3013-3020. https://doi.org/10.1093/bioinformatics/bts569
Uren PJ, Bahrami-Samani E, Burns SC, Qiao M, Karginov FV, Hodges E et al. Site identification in high-throughput RNA-protein interaction data. Bioinformatics. 2012 Dec;28(23):3013-3020. https://doi.org/10.1093/bioinformatics/bts569
Uren, Philip J. ; Bahrami-Samani, Emad ; Burns, Suzanne C. ; Qiao, Mei ; Karginov, Fedor V. ; Hodges, Emily ; Hannon, Gregory J. ; Sanford, Jeremy R. ; Penalva, Luiz O ; Smith, Andrew D. / Site identification in high-throughput RNA-protein interaction data. In: Bioinformatics. 2012 ; Vol. 28, No. 23. pp. 3013-3020.
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