To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("wavClusteR")
In most cases, you don't need to download the package archive at all.
This package is for version 3.2 of Bioconductor; for the stable, up-to-date release version, see wavClusteR.
Bioconductor version: 3.2
A comprehensive 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 bsse.ethz.ch>
Citation (from within R,
enter citation("wavClusteR")):
To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("wavClusteR")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("wavClusteR")
Follow Installation instructions to use this package in your R session.
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