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[![R-CMD-check-bioc](]( [![BioC status](]( [![Platforms](]( [![Coverage](]( [![License: Artistic-2.0](]( # PureCN A tool developed for tumor-only diagnostic sequencing using hybrid-capture protocols. It provides copy number adjusted for purity and ploidy and can classify mutations by somatic status and clonality. It requires a pool of process-matched normals for coverage normalization and artifact filtering. PureCN was parameterized using large collections of diverse samples, ranging from low coverage whole-exome to ultra-deep sequenced plasma gene-panels. ## Installation To install this package, start R and enter: ``` if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("PureCN") ``` If your R/Bioconductor version is [outdated](, this will install an old and unsupported version. For outdated R/Bioconductor versions, you can try backporting the latest stable version (this should work fine for Bioconductor 3.3 and later): ``` BiocManager::install("lima1/PureCN", ref = "RELEASE_3_18") ``` If you want the latest and greatest from the developer branch: ``` BiocManager::install("lima1/PureCN") ``` To get the lastest stable version from [Conda]( (unstable is currently only available from GitHub directly): ``` conda install -c bioconda bioconductor-purecn=2.8.1 ``` A [Dockerhub]( image of the latest stable version with recommended dependencies such as [GenomicsDB]( and [GATK 4]( pre-installed: ``` docker pull markusriester/purecn:latest ``` ## Tutorials To get started: ``` vignette("Quick", package = "PureCN") ``` For the R package and more detailed information: ``` vignette("PureCN", package = "PureCN") ``` These tutorials are also available on the Bioconductor project page ([devel](, [stable]( ## Bugs Before [posting]( a bug report: * update to the latest version * confirm with sessionInfo() that the latest version is used * if this is a first PureCN attempt, closely follow the Quick vignette ([devel](, [stable]( * make sure that the issue is not covered in the Support section of the main vignette ## Papers * Main paper describing the likelihood model: Riester M, Singh A, Brannon A, Yu K, Campbell C, Chiang D and Morrissey M (2016). “PureCN: Copy number calling and SNV classification using targeted short read sequencing.” _Source Code for Biology and Medicine_, **11**, pp. 13. doi: [10.1186/s13029-016-0060-z]( * Validation paper, including description of novel additions, such as off-target support, tangent normalization and tweaks to the likelihood model: Oh S, Geistlinger L, Ramos M, Morgan M, Waldron L, Riester M (2020). Reliable analysis of clinical tumor-only whole exome sequencing data. _JCO Clinical Cancer Informatics_. doi: [10.1200/CCI.19.00130](; _bioRxiv_. doi: [10.1101/552711]( ## Selected citations Pereira et al. (2021). "Cell-free DNA captures tumor heterogeneity and driver alterations in rapid autopsies with pre-treated metastatic cancer". _Nature Communications_. doi: [10.1038/s41467-021-23394-4]( Dummer et al. (2020). "Combined PD-1, BRAF and MEK inhibition in advanced BRAF-mutant melanoma: safety run-in and biomarker cohorts of COMBI-i". _Nature Medicine_. doi: [10.1038/s41591-020-1082-2]( Bertucci et al. (2019). "Genomic characterization of metastatic breast cancers". _Nature_. doi: [10.1038/s41586-019-1056-z]( Dagogo-Jack et al. (2018). "Tracking the evolution of resistance to ALK tyrosine kinase inhibitors through longitudinal analysis of circulating tumor DNA". _JCO Precision Oncology_. doi: [10.1200/PO.17.00160]( Orlando et al. (2018). "Genetic mechanisms of target antigen loss in CAR19 therapy of acute lymphoblastic leukemia". _Nature Medicine_. doi: [10.1038/s41591-018-0146-z]( Pal et al. (2018). "Efficacy of BGJ398, a fibroblast growth factor receptor 1-3 inhibitor, in patients with previously treated advanced urothelial carcinoma with FGFR3 alterations". _Cancer Discovery_. doi: [10.1158/2159-8290.CD-18-0229]( Pitt et al. (2018). "Characterization of Nigerian breast cancer reveals prevalent homologous recombination deficiency and aggressive molecular features". _Nature Communications_. doi: [10.1038/s41467-018-06616-0](