Abstract
We have developed a novel Bayesian method, PurBayes, to estimate tumor purity and detect intratumor heterogeneity based on next-generation sequencing data of paired tumor-normal tissue samples, which uses finite mixture modeling methods. We demonstrate our approach using simulated data and discuss its performance under varying conditions.Availability: PurBayes is implemented as an R package, and source code is available for download through CRAN at http://cran.r-project.org/package=PurBayes.Contact: Supplementary information: Supplementary data are available online at Bioinformatics online. © 2013 The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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CITATION STYLE
Larson, N. B., & Fridley, B. L. (2013). PurBayes: Estimating tumor cellularity and subclonality in next-generation sequencing data. Bioinformatics, 29(15), 1888–1889. https://doi.org/10.1093/bioinformatics/btt293
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