A combinatorial approach for analyzing intra-tumor heterogeneity from high-throughput sequencing data.
A combinatorial approach for analyzing intra-tumor heterogeneity from high-throughput sequencing data.
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DOI：
10.1093/bioinformatics/btu284
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发表时间：
2014-06-15
期刊：
影响因子：
--
通讯作者：
Raphael BJ
中科院分区：
文献类型：
--
作者：
Hajirasouliha I;Mahmoody A;Raphael BJ
动机：肿瘤样本的高通量测序表明，大多数肿瘤表现出广泛的肿瘤内异质性，多个肿瘤细胞亚群含有不同的体细胞突变。最近的研究通过根据观察到的包含变异等位基因的 DNA 测序读数计数将突变聚类到亚群中，量化了肿瘤内的异质性。然而，这些聚类方法没有考虑到不同肿瘤亚群的群体频率与其在同一细胞群体中的共同祖先相关。结果：我们引入了二叉树划分（BTP），这是一种根据体细胞突变的变异等位基因频率构建肿瘤细胞亚群问题的新型组合公式。我们证明寻找 BTP 是一个 NP 完全问题；导出问题优化版本的近似算法；并提出一种递归算法来查找输入中存在错误的 BTP。我们表明，所得到的算法在模拟和真实测序数据上优于现有的聚类方法。可用性和实施：我们方法的 Python 和 MATLAB 实施可在 http://compbio.cs.brown.edu/software/ 联系：braphael@cs.brown.edu 补充信息：补充数据可在生物信息学在线获取。
Motivation: High-throughput sequencing of tumor samples has shown that most tumors exhibit extensive intra-tumor heterogeneity, with multiple subpopulations of tumor cells containing different somatic mutations. Recent studies have quantified this intra-tumor heterogeneity by clustering mutations into subpopulations according to the observed counts of DNA sequencing reads containing the variant allele. However, these clustering approaches do not consider that the population frequencies of different tumor subpopulations are correlated by their shared ancestry in the same population of cells. Results: We introduce the binary tree partition (BTP), a novel combinatorial formulation of the problem of constructing the subpopulations of tumor cells from the variant allele frequencies of somatic mutations. We show that finding a BTP is an NP-complete problem; derive an approximation algorithm for an optimization version of the problem; and present a recursive algorithm to find a BTP with errors in the input. We show that the resulting algorithm outperforms existing clustering approaches on simulated and real sequencing data. Availability and implementation: Python and MATLAB implementations of our method are available at http://compbio.cs.brown.edu/software/ Contact: braphael@cs.brown.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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