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SURF: integrative analysis of a compendium of RNA-seq and CLIP-seq datasets highlights complex governing of alternative transcriptional regulation by RNA-binding proteins

Advances in high-throughput profiling of RNA-binding proteins (RBPs) have resulted inCLIP-seq datasets coupled with transcriptome profiling by RNA-seq. However, analysis methods that integrate both types of data are lacking. We describe SURF, Statistical Utility for RBP Functions, for integrative an...

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Detalles Bibliográficos
Autores principales: Chen, Fan, Keleş, Sündüz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7291511/
https://www.ncbi.nlm.nih.gov/pubmed/32532357
http://dx.doi.org/10.1186/s13059-020-02039-7
Descripción
Sumario:Advances in high-throughput profiling of RNA-binding proteins (RBPs) have resulted inCLIP-seq datasets coupled with transcriptome profiling by RNA-seq. However, analysis methods that integrate both types of data are lacking. We describe SURF, Statistical Utility for RBP Functions, for integrative analysis of large collections of CLIP-seq and RNA-seq data. We demonstrate SURF’s ability to accurately detect differential alternative transcriptional regulation events and associate them to local protein-RNA interactions. We apply SURF to ENCODE RBP compendium and carry out downstream analysis with additional reference datasets. The results of this application are browsable at http://www.statlab.wisc.edu/shiny/surf/.