To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("CNVPanelizer")

In most cases, you don't need to download the package archive at all.

CNVPanelizer

 

   

Reliable CNV detection in targeted sequencing applications

Bioconductor version: Release (3.4)

A method that allows for the use of a collection of non-matched normal tissue samples. Our approach uses a non-parametric bootstrap subsampling of the available reference samples to estimate the distribution of read counts from targeted sequencing. As inspired by random forest, this is combined with a procedure that subsamples the amplicons associated with each of the targeted genes. The obtained information allows us to reliably classify the copy number aberrations on the gene level.

Author: Cristiano Oliveira [aut], Thomas Wolf [aut, cre], Albrecht Stenzinger [ctb], Volker Endris [ctb], Nicole Pfarr [ctb], Benedikt Brors [ths], Wilko Weichert [ths]

Maintainer: Thomas Wolf <thomas_wolf71 at gmx.de>

Citation (from within R, enter citation("CNVPanelizer")):

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("CNVPanelizer")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("CNVPanelizer")

 

PDF R Script CNVPanelizer
PDF   Reference Manual
Text   NEWS

Details

biocViews Classification, CopyNumberVariation, Coverage, Normalization, Sequencing, Software
Version 1.4.0
In Bioconductor since BioC 3.2 (R-3.2) (1.5 years)
License GPL-3
Depends R (>= 3.2.0), GenomicRanges
Imports S4Vectors, grDevices, stats, utils, NOISeq, IRanges, Rsamtools, exomeCopy, foreach, ggplot2, plyr, openxlsx
LinkingTo
Suggests knitr, RUnit, BiocGenerics
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Package Source CNVPanelizer_1.4.0.tar.gz
Windows Binary CNVPanelizer_1.4.0.zip
Mac OS X 10.9 (Mavericks) CNVPanelizer_1.4.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/CNVPanelizer/tree/release-3.4
Package Short Url http://bioconductor.org/packages/CNVPanelizer/
Package Downloads Report Download Stats

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