dCLIP: a computational approach for comparative CLIP-seq analyses

Genome Biol. 2014 Jan 7;15(1):R11. doi: 10.1186/gb-2014-15-1-r11.

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/.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Computational Biology / methods*
  • HEK293 Cells
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • Immunoprecipitation / methods*
  • Linear Models
  • Mice
  • MicroRNAs / genetics
  • MicroRNAs / metabolism
  • Models, Theoretical
  • RNA-Binding Proteins / genetics
  • RNA-Binding Proteins / metabolism
  • Sequence Analysis, RNA / methods*
  • Software

Substances

  • MIRN124 microRNA, human
  • MicroRNAs
  • Mirn155 microRNA, mouse
  • RNA-Binding Proteins