Darvesh Gorhe

I am a PhD candidate in the lab of Marko Jovanovic working on modeling crosslinking and immunoprecipitation sequencing (CLIP-seq) data using stochastic processes and mixture models.

CLIP-seq gives us the RNA sequences bound by RNA-binding proteins in vivo using UV crosslinking followed by antibody pulldown(s) and sequencing. Many labs have contributed to CLIP-seq variants that make the detection of RNA species bound to RBPs more sensitive (iCLIP, eCLIP), more specific (easyCLIP, PAR-CLIP), and more multiplexed (SPIDR, ABC). Many methods have been developed to analyze this data (Skipper, CIMS, Piranha, PureCLIP, omniCLIP, etc) that aim to tell us: what information about RBP-binding behavior do we get from CLIP-seq? In particular, what information can we get from CLIP-seq that cannot be found by other methods? My work aims to address this question by looking at the distribution of crosslink spacing rather than the concentration of crosslinking events within a window.