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dCLIP: a computational approach for comparative CLIP-seq analyses
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 e...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4054096/ https://www.ncbi.nlm.nih.gov/pubmed/24398258 http://dx.doi.org/10.1186/gb-2014-15-1-r11 |
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author | Wang, Tao Xie, Yang Xiao, Guanghua |
author_facet | Wang, Tao Xie, Yang Xiao, Guanghua |
author_sort | Wang, Tao |
collection | PubMed |
description | 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/. |
format | Online Article Text |
id | pubmed-4054096 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40540962014-06-12 dCLIP: a computational approach for comparative CLIP-seq analyses Wang, Tao Xie, Yang Xiao, Guanghua Genome Biol Software 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/. BioMed Central 2014 2014-01-07 /pmc/articles/PMC4054096/ /pubmed/24398258 http://dx.doi.org/10.1186/gb-2014-15-1-r11 Text en Copyright © 2014 Wang et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Wang, Tao Xie, Yang Xiao, Guanghua dCLIP: a computational approach for comparative CLIP-seq analyses |
title | dCLIP: a computational approach for comparative CLIP-seq analyses |
title_full | dCLIP: a computational approach for comparative CLIP-seq analyses |
title_fullStr | dCLIP: a computational approach for comparative CLIP-seq analyses |
title_full_unstemmed | dCLIP: a computational approach for comparative CLIP-seq analyses |
title_short | dCLIP: a computational approach for comparative CLIP-seq analyses |
title_sort | dclip: a computational approach for comparative clip-seq analyses |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4054096/ https://www.ncbi.nlm.nih.gov/pubmed/24398258 http://dx.doi.org/10.1186/gb-2014-15-1-r11 |
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