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Bioconductor - wavClusteR

wavClusteR

This is the released version of wavClusteR; for the devel version, see wavClusteR.

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

Bioconductor version: Release (3.21)

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 gmail.com>

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

To install this package, start R (version "4.5") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("wavClusteR")

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

Documentation

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

browseVignettes("wavClusteR")
Details biocViews Bayesian, ImmunoOncology, RIPSeq, RNASeq, Sequencing, Software, Technology Version 2.42.0 In Bioconductor since BioC 3.0 (R-3.1) (10.5 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 URL See More Package Archives

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

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