wavClusteR: Sensitive and highly resolved identification of RNA-protein interaction sites in PAR-CLIP data
Version 2.11.0

The package provides an integrated pipeline for the analysis of PAR-CLIP data. PAR-CLIP-induced transitions are first discriminated from sequencing errors, SNPs and additional non-experimental sources by a non- parametric mixture model. The protein binding sites (clusters) are then resolved at high resolution and cluster statistics are estimated using a rigorous Bayesian framework. Post-processing of the results, data export for UCSC genome browser visualization and motif search analysis are provided. In addition, the package allows to integrate RNA-Seq data to estimate the False Discovery Rate of cluster detection. Key functions support parallel multicore computing. Note: while wavClusteR was designed for PAR-CLIP data analysis, it can be applied to the analysis of other NGS data obtained from experimental procedures that induce nucleotide substitutions (e.g. BisSeq).

Package details

AuthorFederico Comoglio and Cem Sievers
Bioconductor views Bayesian RIPSeq RNASeq Sequencing Technology
MaintainerFederico Comoglio <[email protected]>
LicenseGPL-2
Version2.11.0
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("wavClusteR")

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wavClusteR documentation built on Nov. 17, 2017, 9:16 a.m.