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 (3.23)
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("wavClusteR")):
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.
Installation
To install this package, start R (version "4.6") 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")| wavClusteR: a workflow for PAR-CLIP data analysis | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | Bayesian, ImmunoOncology, RIPSeq, RNASeq, Sequencing, Software, Technology |
| Version | 2.46.0 |
| In Bioconductor since | BioC 3.0 (R-3.1) (12 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, txdbmaker |
| System Requirements | |
| URL |
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_2.46.0.tar.gz |
| Windows Binary (x86_64) | wavClusteR_2.46.0.zip |
| macOS Binary (big-sur-x86_64) | wavClusteR_2.46.0.tgz |
| macOS Binary (sonoma-arm64) | wavClusteR_2.46.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/wavClusteR |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/wavClusteR |
| Bioc Package Browser | https://code.bioconductor.org/browse/wavClusteR/ |
| Package Short Url | https://bioconductor.org/packages/wavClusteR/ |
| Package Downloads Report | Download Stats |