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Bioinformatics. 2013 Oct 1;29(19):2485-6. doi: 10.1093/bioinformatics/btt428. Epub 2013 Aug 8.

ASPeak: an abundance sensitive peak detection algorithm for RIP-Seq.

Author information

  • 1Department of Biochemistry and Molecular Pharmacology, Howard Hughes Medical Institute, University of Massachusetts Medical School, Worcester, MA 01605 and Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.

Abstract

SUMMARY:

Unlike DNA, RNA abundances can vary over several orders of magnitude. Thus, identification of RNA-protein binding sites from high-throughput sequencing data presents unique challenges. Although peak identification in ChIP-Seq data has been extensively explored, there are few bioinformatics tools tailored for peak calling on analogous datasets for RNA-binding proteins. Here we describe ASPeak (abundance sensitive peak detection algorithm), an implementation of an algorithm that we previously applied to detect peaks in exon junction complex RNA immunoprecipitation in tandem experiments. Our peak detection algorithm yields stringent and robust target sets enabling sensitive motif finding and downstream functional analyses.

AVAILABILITY:

ASPeak is implemented in Perl as a complete pipeline that takes bedGraph files as input. ASPeak implementation is freely available at https://sourceforge.net/projects/as-peak under the GNU General Public License. ASPeak can be run on a personal computer, yet is designed to be easily parallelizable. ASPeak can also run on high performance computing clusters providing efficient speedup. The documentation and user manual can be obtained from http://master.dl.sourceforge.net/project/as-peak/manual.pdf.

PMID:
23929032
PMCID:
PMC3777114
DOI:
10.1093/bioinformatics/btt428
[PubMed - indexed for MEDLINE]
Free PMC Article
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