recipe bioconductor-wavcluster

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

Homepage:

https://bioconductor.org/packages/3.16/bioc/html/wavClusteR.html

License:

GPL-2

Recipe:

/bioconductor-wavcluster/meta.yaml

Links:

biotools: wavcluster

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).

package bioconductor-wavcluster

Versions:

2.32.0-0,  2.28.0-0,  2.26.0-0,  2.24.0-1,  2.24.0-0,  2.22.0-0,  2.20.0-0,  2.18.0-1,  2.16.0-0, 

2.32.0-0,  2.28.0-0,  2.26.0-0,  2.24.0-1,  2.24.0-0,  2.22.0-0,  2.20.0-0,  2.18.0-1,  2.16.0-0,  2.14.0-0,  2.11.0-0

Depends:

• bioconductor-biocgenerics >=0.44.0,<0.45.0

• bioconductor-biostrings >=2.66.0,<2.67.0

• bioconductor-genomicfeatures >=1.50.0,<1.51.0

• bioconductor-genomicranges >=1.50.0,<1.51.0

• bioconductor-iranges >=2.32.0,<2.33.0

• bioconductor-rsamtools >=2.14.0,<2.15.0

• bioconductor-rtracklayer >=1.58.0,<1.59.0

• bioconductor-s4vectors >=0.36.0,<0.37.0

• r-base >=4.2,<4.3.0a0

• r-foreach

• r-ggplot2

• r-hmisc

• r-mclust

• r-seqinr

• r-stringr

Required By:

Installation

With an activated Bioconda channel (see set-up-channels), install with:

conda install bioconductor-wavcluster

and update with:

conda update bioconductor-wavcluster

or use the docker container:

docker pull quay.io/biocontainers/bioconductor-wavcluster:<tag>

(see bioconductor-wavcluster/tags for valid values for <tag>)

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