Reliable CNV detection in targeted sequencing applications
conda install -c bioconda bioconductor-cnvpanelizer
conda install -c bioconda/label/gcc7 bioconductor-cnvpanelizer
conda install -c bioconda/label/cf201901 bioconductor-cnvpanelizer
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.