Mixture models and wavelet transforms reveal high confidence RNA-protein 
interaction sites in MoV10PAR-CLIP data

Sievers, Cem; Schlumpf, Tommy; Sawarkar, Ritwick; Comoglio, Federico; Paro, Renato

doi:org/10.1093/nar/gks697

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Mixture models and wavelet transforms reveal high confidence RNA-protein interaction sites in MoV10PAR-CLIP data

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Sawarkar, Ritwick
Max Planck Institute of Immunobiology and Epigenetics, Max Planck Society;

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https://academic.oup.com/nar/article/40/20/e160/2414476
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Citation

Sievers, C., Schlumpf, T., Sawarkar, R., Comoglio, F., & Paro, R. (2012). Mixture models and wavelet transforms reveal high confidence RNA-protein interaction sites in MoV10PAR-CLIP data. Nucleic Acids Research (London), 40, e160. doi:org/10.1093/nar/gks697.

Cite as: https://hdl.handle.net/21.11116/0000-0006-9E95-0

Abstract

The Photo-Activatable Ribonucleoside-enhanced CrossLinking and ImmunoPrecipitation (PAR-CLIP) method was recently developed for global identification of RNAs interacting with proteins. The strength of this versatile method results from induction of specific T to C transitions at sites of interaction. However, current analytical tools do not distinguish between non-experimentally and experimentally induced transitions. Furthermore, geometric properties at potential binding sites are not taken into account. To surmount these shortcomings, we developed a two-step algorithm consisting of a non-parametric two-component mixture model and a wavelet-based peak calling procedure. Our algorithm can reduce the number of false positives up to 24% thereby identifying high confidence interaction sites. We successfully employed this approach in conjunction with a modified PAR-CLIP protocol to study the functional role of nuclear Moloney leukemia virus 10, a putative RNA helicase interacting with Argonaute2 and Polycomb. Our method, available as the R package wavClusteR , is generally applicable to any substitution-based inference problem in genomics.