AbsCN-seq: a statistical method to estimate tumor purity, ploidy and absolute copy numbers from next-generation sequencing data.

TitleAbsCN-seq: a statistical method to estimate tumor purity, ploidy and absolute copy numbers from next-generation sequencing data.
Publication TypeJournal Article
Year of Publication2014
AuthorsBao, L, Pu, M, Messer, K
JournalBioinformatics
Date Published2014 Jan 13
ISSN1367-4811
iDASH CategoryData Analysis and Compression
AbstractMOTIVATION: Detection and quantification of the absolute DNA copy number alterations in tumor cells is challenging because the DNA specimen is extracted from a mixture of tumor and normal stromal cells. Estimates of tumor purity and ploidy are necessary to correctly infer copy number, and ploidy may itself be a prognostic factor in cancer progression. As deep sequencing of the exome or genome has become routine for characterization of tumor samples, in this work, we aim to develop a simple and robust algorithm to infer purity, ploidy and absolute copy numbers in whole numbers for tumor cells from sequencing data. RESULTS: A simulation study shows that estimates have reasonable accuracy, and that the algorithm is robust against the presence of segmentation errors and subclonal populations. We validated our algorithm against a panel of cell lines with experimentally determined ploidy. We also compared our algorithm with the well-established single-nucleotide polymorphism array-based method called ABSOLUTE on three sets of tumors of different types. Our method had good performance on these four benchmark datasets for both purity and ploidy estimates, and may offer a simple solution to copy number alteration quantification for cancer sequencing projects.Availability and implementation: The R package absCNseq is available from http://biostats.mcc.ucsd.edu/files/absCNseq_1.0.tar.gz. CONTACT: kmesser@ucsd.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
DOI10.1093/bioinformatics/btt759
Alternate JournalBioinformatics
PubMed ID24389661

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