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.