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

被引：69

作者：

Larson, Nicholas B. ^{[1
]}

Fridley, Brooke L. ^{[2
]}

机构：

[1] Mayo Clin, Div Biomed Stat & Informat, Dept Hlth Sci Res, Rochester, MN 55901 USA

[2] Univ Kansas, Med Ctr, Dept Biostat, Kansas City, KS 66160 USA

来源：

BIOINFORMATICS | 2013年 / 29卷 / 15期

关键词：

D O I：

10.1093/bioinformatics/btt293

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

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.

引用

页码：1888 / 1889

页数：2

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