{ "_id": "6a196598acfb0bcc41de6df9", "Package": "CNVPanelizer", "Type": "Package", "Title": "Reliable CNV detection in targeted sequencing applications", "Version": "1.44.0", "Date": "2023-03-28", "Authors@R": "c(\nperson(\"Cristiano\", \"Oliveira\", email = \"tanovsky@gmail.com\", role = c(\"aut\")),\nperson(\"Thomas\", \"Wolf\", email = \"thomas_wolf71@gmx.de\", role = c(\"aut\", \"cre\")),\nperson(\"Albrecht\", \"Stenzinger\", email = \"albrecht.stenzinger@med.uni-heidelberg.de\", role = c(\"ctb\")),\nperson(\"Volker\", \"Endris\", email = \"volker.endris@med.uni-heidelberg.de\", role = c(\"ctb\")),\nperson(\"Nicole\", \"Pfarr\", email = \"nicole.pfarr@med.uni-heidelberg.de\", role = c(\"ctb\")),\nperson(\"Benedikt\", \"Brors\", email = \"b.brors@dkfz.de\", role = c(\"ths\")),\nperson(\"Wilko\", \"Weichert\", email = \"wilko.weichert@med.uni-heidelberg.de\", role = c(\"ths\")))", "Description": "A method that allows for the use of a collection of\nnon-matched normal tissue samples. Our approach uses a\nnon-parametric bootstrap subsampling of the available reference\nsamples to estimate the distribution of read counts from\ntargeted sequencing. As inspired by random forest, this is\ncombined with a procedure that subsamples the amplicons\nassociated with each of the targeted genes. 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