Mixture models and wavelet transforms reveal high confidence RNA-protein interaction sites in MOV10 PAR-CLIP data
- PMID: 22844102
- PMCID: PMC3488208
- DOI: 10.1093/nar/gks697
Mixture models and wavelet transforms reveal high confidence RNA-protein interaction sites in MOV10 PAR-CLIP data
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.
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