title: dCLIP: a computational approach for comparative CLIP-seq analyses.
abstract: Although comparison of RNA-protein interaction profiles across different conditions has become increasingly important to understanding the function of RNA-binding proteins (RBPs), few computational approaches have been developed for quantitative comparison of CLIP-seq datasets. Here, we present an easy-to-use command line tool, dCLIP, for quantitative CLIP-seq comparative analysis. The two-stage method implemented in dCLIP, including a modified MA normalization method and a hidden Markov model, is shown to be able to effectively identify differential binding regions of RBPs in four CLIP-seq datasets, generated by HITS-CLIP, iCLIP and PAR-CLIP protocols. dCLIP is freely available at http://qbrc.swmed.edu/software/.
authors.forename: Tao
authors.initials: T
authors.lastname: Wang
authors.forename: Yang
authors.initials: Y
authors.lastname: Xie
authors.forename: Guanghua
authors.initials: G
authors.lastname: Xiao
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods*; D057809:HEK293 Cells; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D047468:Immunoprecipitation / Q000379:methods*; D016014:Linear Models; D051379:Mice; D035683:MicroRNAs / Q000235:genetics / Q000378:metabolism; D008962:Models, Theoretical; D016601:RNA-Binding Proteins / Q000235:genetics / Q000378:metabolism; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software
chemical_list: C509207:MIRN124 microRNA, human; D035683:MicroRNAs; C532623:Mirn155 microRNA, mouse; D016601:RNA-Binding Proteins