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CNVPanelizer

Reliable CNV detection in targeted sequencing applications

Bioconductor version: 3.23 · Package version: 1.44.0

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.

Installation

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

BiocManager::install("CNVPanelizer")

Details

MaintainerThomas Wolf <thomas_wolf71@gmx.de>
AuthorCristiano Oliveira [aut], Thomas Wolf [aut, cre], Albrecht Stenzinger [ctb], Volker Endris [ctb], Nicole Pfarr [ctb], Benedikt Brors [ths], Wilko Weichert [ths]
LicenseGPL-3
Downloads rank370
Source branchRELEASE_3_23
biocViewsClassification, CopyNumberVariation, Coverage, Normalization, Sequencing, Software

Documentation

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Dependencies

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

Suggests: knitr, RUnit