AbsCN-seq

MOTIVATION: 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.

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

AbsCN-seq is an R package for estimation of tumor purity, ploidy, and copy number variation (CNV) in next-generation sequencing data.

AbsCN-seq

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