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CNVPanelizer

This package is deprecated. It will probably be removed from Bioconductor. Please refer to the package end-of-life guidelines for more information.

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

Reliable CNV detection in targeted sequencing applications


Bioconductor version: Development (3.19)

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 "4.4") 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

Reference Manual PDF

Details

biocViews Classification, CopyNumberVariation, Coverage, Normalization, Sequencing, Software
Version 1.35.1
In Bioconductor since BioC 3.2 (R-3.2) (8.5 years)
License GPL-3
Depends R (>= 3.2.0), GenomicRanges
Imports BiocGenerics, S4Vectors, grDevices, stats, utils, NOISeq, IRanges, Rsamtools, exomeCopy, 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
Windows Binary
macOS Binary (x86_64)
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
Package Short Url https://bioconductor.org/packages/CNVPanelizer/
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