TY - JOUR
T1 - dCLIP
T2 - A computational approach for comparative CLIP-seq analyses
AU - Wang, Tao
AU - Xie, Yang
AU - Xiao, Guanghua
PY - 2014
Y1 - 2014
N2 - 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/.
AB - 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/.
UR - http://www.scopus.com/inward/record.url?scp=84892171302&partnerID=8YFLogxK
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U2 - 10.1186/gb-2014-15-1-r11
DO - 10.1186/gb-2014-15-1-r11
M3 - Article
C2 - 24398258
AN - SCOPUS:84892171302
VL - 15
JO - Genome Biology
JF - Genome Biology
SN - 1474-7596
IS - 1
M1 - R11
ER -