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PARalyzer: definition of RNA binding sites from PAR-CLIP short-read sequence data

David L Corcoran1, Stoyan Georgiev12, Neelanjan Mukherjee1, Eva Gottwein34, Rebecca L Skalsky5, Jack D Keene5 and Uwe Ohler16*

Author Affiliations

1 Institute for Genome Sciences and Policy, Duke University, 101 Science Drive, CIEMAS 2171, Box 3382, Durham, NC 27708, USA

2 Program for Computational Biology and Bioinformatics, Duke University, 102 North Building, Durham, NC 27708, USA

3 Department of Microbiology-Immunology, Feinberg School of Medicine, Northwestern University, 310 E. Chicago Ave, Chicago, IL 60611, USA

4 Department of Microbiology-Immunology, Feinberg School of Medicine, Northwestern University, 320 E. Superior, Chicago IL 60611, USA

5 Department of Molecular Genetics and Microbiology, Duke University Medical Center, 268 CARL Building, Box 3054 DUMC, Durham, NC 27710, USA

6 Department of Biostatistics and Bioinformatics, Duke University, 2424 Erwin Road, Suite 1102 Hock Plaza, Box 2721, Durham, NC 27710, USA

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Genome Biology 2011, 12:R79  doi:10.1186/gb-2011-12-8-r79

Published: 18 August 2011


Crosslinking and immunoprecipitation (CLIP) protocols have made it possible to identify transcriptome-wide RNA-protein interaction sites. In particular, PAR-CLIP utilizes a photoactivatable nucleoside for more efficient crosslinking. We present an approach, centered on the novel PARalyzer tool, for mapping high-confidence sites from PAR-CLIP deep-sequencing data. We show that PARalyzer delineates sites with a high signal-to-noise ratio. Motif finding identifies the sequence preferences of RNA-binding proteins, as well as seed-matches for highly expressed microRNAs when profiling Argonaute proteins. Our study describes tailored analytical methods and provides guidelines for future efforts to utilize high-throughput sequencing in RNA biology. PARalyzer is available at webcite.