PurBayes: estimating tumor cellularity and subclonality in next-generation sequencing data

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 i...

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Bibliographic Details
Published in:Bioinformatics 2013-08, Vol.29 (15), p.1888-1889
Main Authors: Larson, Nicholas B, Fridley, Brooke L
Format: Article
Language:English
Subjects:
Applications Notes
Bayes Theorem
Genetic Variation
High-Throughput Nucleotide Sequencing
Humans
Neoplasms - genetics
Software
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Summary: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. PurBayes is implemented as an R package, and source code is available for download through CRAN at http://cran.r-project.org/package=PurBayes. larson.nicholas@mayo.edu Supplementary data are available online at Bioinformatics online.
ISSN:1367-4803
1367-4811
1460-2059
DOI:10.1093/bioinformatics/btt293