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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.
Package details |
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Author | Cristiano 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 |
Maintainer | Thomas Wolf <thomas_wolf71@gmx.de> |
License | GPL-3 |
Version | 1.22.0 |
Package repository | View on Bioconductor |
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