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A statistical and computational framework for PAR-CLIP data analysis. A sensitive transition-centered algorithm specifically designed to resolve protein binding sites at high resolution in PAR-CLIP data was developed. This method employes a Bayesian network approach to associate posterior log-odds with the observed transitions, providing an overall quantification of the confidence in RNA-protein interaction.

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wavClusteR forum

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wavClusteR classification

wavClusteR specifications

Unique identifier:
OMICS_02255
Interface:
Command line interface
Input format:
BAM
Programming languages:
R
Version:
2.1.0
Requirements:
GenomicRanges, Rsamtools
Software type:
Package/Module
Restrictions to use:
None
Operating system:
Unix/Linux, Mac OS, Windows
Computer skills:
Advanced
Stability:
Stable
Maintained:
Yes

wavClusteR distribution

versioning

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No versioning.

wavClusteR support

Documentation

Maintainer

  • Federico Comoglio <>

Credits

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Publications

Institution(s)

Department of Biosystems Science and Engineering, Swiss Federal Institute of Technology Zurich, Basel, Switzerland

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