recipe bioconductor-wavcluster

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







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

(downloads) docker_bioconductor-wavcluster



Required By


With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-wavcluster

and update with:

conda update bioconductor-wavcluster

or use the docker container:

docker pull<tag>

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