CNVPanelizer: Reliable CNV detection in targeted sequencing applications

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.

Install the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("CNVPanelizer")
AuthorCristiano Oliveira [aut], Thomas Wolf [aut, cre], Albrecht Stenzinger [ctb], Volker Endris [ctb], Nicole Pfarr [ctb], Benedikt Brors [ths], Wilko Weichert [ths]
Bioconductor views Classification CopyNumberVariation Coverage Normalization Sequencing
Date of publicationNone
MaintainerThomas Wolf <thomas_wolf71@gmx.de>
LicenseGPL-3
Version1.6.0

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