Package: wavClusteR
Type: Package
Title: Sensitive and highly resolved identification of RNA-protein
        interaction sites in PAR-CLIP data
Version: 2.20.0
Date: 2015-05-07
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, wmtsa
Suggests: BiocStyle, knitr, rmarkdown, BSgenome.Hsapiens.UCSC.hg19
Enhances: doMC
VignetteBuilder: knitr
Author: Federico Comoglio and Cem Sievers
Maintainer: Federico Comoglio <federico.comoglio@gmail.com>
Description: 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).
License: GPL-2
biocViews: ImmunoOncology, Sequencing, Technology, RIPSeq, RNASeq,
        Bayesian
LazyLoad: yes
RoxygenNote: 5.0.1
git_url: https://git.bioconductor.org/packages/wavClusteR
git_branch: RELEASE_3_10
git_last_commit: f791050
git_last_commit_date: 2019-10-29
Date/Publication: 2019-10-29
NeedsCompilation: no
Packaged: 2019-10-30 02:41:43 UTC; biocbuild
Built: R 3.6.1; ; 2019-10-30 14:24:39 UTC; windows
