Registration Open for Bioc2024 July 24-26


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 (3.20)

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>

Citation (from within R, enter citation("wavClusteR")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

wavClusteR: a workflow for PAR-CLIP data analysis HTML R Script
Reference Manual PDF


biocViews Bayesian, ImmunoOncology, RIPSeq, RNASeq, Sequencing, Software, Technology
Version 2.39.0
In Bioconductor since BioC 3.0 (R-3.1) (10 years)
License GPL-2
Depends R (>= 3.2), GenomicRanges(>= 1.31.8), Rsamtools
Imports methods, BiocGenerics, S4Vectors(>= 0.17.25), IRanges(>= 2.13.12), Biostrings(>= 2.47.6), foreach, GenomicFeatures(>= 1.31.3), ggplot2, Hmisc, mclust, rtracklayer(>= 1.39.7), seqinr, stringr
System Requirements
See More
Suggests BiocStyle, knitr, rmarkdown, BSgenome.Hsapiens.UCSC.hg19
Linking To
Enhances doMC
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package wavClusteR_2.39.0.tar.gz
Windows Binary
macOS Binary (x86_64) wavClusteR_2.39.0.tgz
macOS Binary (arm64) wavClusteR_2.39.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
Bioc Package Browser
Package Short Url
Package Downloads Report Download Stats