生物
聚类分析
计算生物学
体细胞
遗传学
人口
贝叶斯概率
近似贝叶斯计算
统计推断
推论
癌症的体细胞进化
计算机科学
进化生物学
统计
癌症
人工智能
基因
数学
人口学
社会学
作者
Andrew Roth,Jaswinder Khattra,Damian Yap,Adrian Wan,Emma Laks,Justina Biele,Gavin Ha,Samuel Aparício,Alexandre Bouchard‐Côté,Sohrab P. Shah
出处
期刊:Nature Methods
[Springer Nature]
日期:2014-03-16
卷期号:11 (4): 396-398
被引量:921
摘要
The hierarchical Bayesian model identifies and quantifies clonal populations in tumors from deep-sequenced somatic mutations. We introduce PyClone, a statistical model for inference of clonal population structures in cancers. PyClone is a Bayesian clustering method for grouping sets of deeply sequenced somatic mutations into putative clonal clusters while estimating their cellular prevalences and accounting for allelic imbalances introduced by segmental copy-number changes and normal-cell contamination. Single-cell sequencing validation demonstrates PyClone's accuracy.
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