Package: CNVPanelizer
Type: Package
Title: Reliable CNV detection in targeted sequencing applications
Version: 1.45.0
Date: 2023-03-28
Authors@R: c(
    person("Cristiano", "Oliveira", email = "tanovsky@gmail.com", role = c("aut")),
    person("Thomas", "Wolf", email = "thomas_wolf71@gmx.de", role = c("aut", "cre")),
    person("Albrecht", "Stenzinger", email = "albrecht.stenzinger@med.uni-heidelberg.de", role = c("ctb")),
    person("Volker", "Endris", email = "volker.endris@med.uni-heidelberg.de", role = c("ctb")),
    person("Nicole", "Pfarr", email = "nicole.pfarr@med.uni-heidelberg.de", role = c("ctb")),
    person("Benedikt", "Brors", email = "b.brors@dkfz.de", role = c("ths")),
    person("Wilko", "Weichert", email = "wilko.weichert@med.uni-heidelberg.de", role = c("ths")))
Description: 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.
Depends: R (>= 3.2.0), GenomicRanges
Suggests: knitr, RUnit
Imports: BiocGenerics, S4Vectors, grDevices, stats, utils, NOISeq,
        IRanges, Rsamtools, foreach, ggplot2, plyr, GenomeInfoDb,
        gplots, reshape2, stringr, testthat, graphics, methods, shiny,
        shinyFiles, shinyjs, grid, openxlsx
License: GPL-3
LazyData: false
biocViews: Classification, Sequencing, Normalization,
        CopyNumberVariation, Coverage
VignetteBuilder: knitr
NeedsCompilation: no
Config/pak/sysreqs: cmake make libbz2-dev libicu-dev liblzma-dev
        libuv1-dev libssl-dev xz-utils zlib1g-dev
Repository: https://bioc.r-universe.dev
Date/Publication: 2026-04-28 12:41:28 UTC
RemoteUrl: https://github.com/bioc/CNVPanelizer
RemoteRef: HEAD
RemoteSha: f1d71f9de0a14689a021df66775dd5dc06b5f6eb
Packaged: 2026-07-03 23:33:41 UTC; root
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@gmx.de>