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This is the development version of wavClusteR; for the stable release version, see wavClusteR.

Sensitive and highly resolved identification of RNA-protein interaction sites in PAR-CLIP data

Bioconductor version: Development (3.6)

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).

Author: Federico Comoglio and Cem Sievers

Maintainer: Federico Comoglio <federico.comoglio at>

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HTML R Script wavClusteR: a workflow for PAR-CLIP data analysis
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biocViews Bayesian, RIPSeq, RNASeq, Sequencing, Software, Technology
Version 2.11.0
In Bioconductor since BioC 3.0 (R-3.1) (2.5 years)
License GPL-2
Depends R (>= 3.2), GenomicRanges(>= 1.23.16), Rsamtools
Imports methods, BiocGenerics, S4Vectors(>= 0.9.25), IRanges(>= 2.5.27), Biostrings, foreach, GenomicFeatures, ggplot2, Hmisc, mclust, rtracklayer, seqinr, stringr, wmtsa
Suggests BiocStyle, knitr, rmarkdown, BSgenome.Hsapiens.UCSC.hg19
Enhances doMC
Depends On Me
Imports Me
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