CNVPanelizer

This is the development version of CNVPanelizer; for the stable release version, see CNVPanelizer.

Reliable CNV detection in targeted sequencing applications


Bioconductor version: Development (3.21)

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 (version "4.5") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("CNVPanelizer")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

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

browseVignettes("CNVPanelizer")
CNVPanelizer PDF R Script
Reference Manual PDF
NEWS Text

Details

biocViews Classification, CopyNumberVariation, Coverage, Normalization, Sequencing, Software
Version 1.39.0
In Bioconductor since BioC 3.2 (R-3.2) (9 years)
License GPL-3
Depends R (>= 3.2.0), GenomicRanges
Imports BiocGenerics, S4Vectors, grDevices, stats, utils, NOISeq, IRanges, Rsamtools, foreach, ggplot2, plyr, GenomeInfoDb, gplots, reshape2, stringr, testthat, graphics, methods, shiny, shinyFiles, shinyjs, grid, openxlsx
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Package Archives

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

Source Package CNVPanelizer_1.39.0.tar.gz
Windows Binary (x86_64) CNVPanelizer_1.39.0.zip
macOS Binary (x86_64) CNVPanelizer_1.39.0.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/CNVPanelizer
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/CNVPanelizer
Bioc Package Browser https://code.bioconductor.org/browse/CNVPanelizer/
Package Short Url https://bioconductor.org/packages/CNVPanelizer/
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