Meltos: multi-sample tumor phylogeny reconstruction for structural variants
Meltos: multi-sample tumor phylogeny reconstruction for structural variants
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DOI：
10.1093/bioinformatics/btz737
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发表时间：
2020-02-15
期刊：
影响因子：
5.8
通讯作者：
Hajirasouliha, Iman
中科院分区：
文献类型：
--
作者：
Ricketts, Camir;Seidman, Daniel;Hajirasouliha, Iman
动机：我们提出了Meltos，一种新的计算框架，以解决具有挑战性的问题，建立肿瘤发生树使用体细胞结构变异（SV）之间的多个样本。Meltos利用基于体细胞单核苷酸变异（SNV）构建的肿瘤谱系树，使用新型优化配方鉴定高置信度SV并生成全面的肿瘤谱系树。虽然我们不认为SV的进化进程必然与SNV相同，但我们表明，使用高质量体细胞SNV的肿瘤发生树可以作为在树上调用和分配体细胞SV的指南。Meltos利用多个基因组阅读信号的潜在SV断点在全基因组测序数据，并提出了一个概率公式估计变异等位基因分数（VAFs）的SV events.Results：为了评估Meltos的能力，正确地完善SNV树与SV信息，我们测试了Meltos在两个模拟数据集与5个基因组。我们还在两个真实的癌症数据集上评估了Meltos。我们在来自脂肪肉瘤肿瘤的多个样品和多个样品乳腺癌数据上测试了Meltos（Yates等人，2015），其中作者提供了经验证的结构变异事件以及体细胞SNV集合的深度靶向测序。我们表明Meltos有能力将高置信度验证的SV调用放置在精细的肿瘤发生树上。我们还展示了Meltos的灵活性，可以直接从基因组数据估计VAF，也可以使用拷贝数校正的估计值。
Motivation: We propose Meltos, a novel computational framework to address the challenging problem of building tumor phylogeny trees using somatic structural variants (SVs) among multiple samples. Meltos leverages the tumor phylogeny tree built on somatic single nucleotide variants (SNVs) to identify high confidence SVs and produce a comprehensive tumor lineage tree, using a novel optimization formulation. While we do not assume the evolutionary progression of SVs is necessarily the same as SNVs, we show that a tumor phylogeny tree using high-quality somatic SNVs can act as a guide for calling and assigning somatic SVs on a tree. Meltos utilizes multiple genomic read signals for potential SV breakpoints in whole genome sequencing data and proposes a probabilistic formulation for estimating variant allele fractions (VAFs) of SV events.Results: In order to assess the ability of Meltos to correctly refine SNV trees with SV information, we tested Meltos on two simulated datasets with five genomes in both. We also assessed Meltos on two real cancer datasets. We tested Meltos on multiple samples from a liposarcoma tumor and on a multi-sample breast cancer data (Yates et al., 2015), where the authors provide validated structural variation events together with deep, targeted sequencing for a collection of somatic SNVs. We show Meltos has the ability to place high confidence validated SV calls on a refined tumor phylogeny tree. We also showed the flexibility of Meltos to either estimate VAFs directly from genomic data or to use copy number corrected estimates.