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]|
|Date of publication||None|
|Maintainer||Thomas Wolf <email@example.com>|
CNVPanelizer-package: Reliable CNV detection in targeted sequencing applications
referenceReadCounts: Reference sample data
sampleReadCounts: Test sample data