体细胞突变阶段有助于我们理解癌症相关事件，例如驱动突变。我们为来自 14 名多发性骨髓瘤 (MM) 患者的跨疾病阶段的 23 个样本生成了链接读取全基因组测序数据，并使用链接读取系统地将体细胞突变分配给单倍型。在这里，我们报告了来自多个 MM 样本的重建癌症单倍型和相块，并展示了如何通过整合来自同一个体的样本来扩展相块长度。我们还发现了 MM 中经常突变的基因的定相信息，包括 DIS3 、 HIST1H1E 、 KRAS 、 NRAS 和 TP53 ，对 20,705 个高置信度体细胞突变中的 79.4% 进行了定相。在某些情况下，这使我们能够使用成对的分阶段体细胞突变以更高分辨率解释克隆进化模型。例如，我们对一名患者的分析表明，两个 NRAS 热点突变发生在同一单倍型上，但在不同的亚克隆中是独立事件。鉴于足够的肿瘤纯度和数据质量，我们的框架说明了癌症体细胞突变的单倍型感知分析如何对某些癌症病例有益。

Somatic mutation phasing informs our understanding of cancer-related events, like driver mutations. We generated linked-read whole genome sequencing data for 23 samples across disease stages from 14 multiple myeloma (MM) patients and systematically assigned somatic mutations to haplotypes using linked-reads. Here, we report the reconstructed cancer haplotypes and phase blocks from several MM samples and show how phase block length can be extended by integrating samples from the same individual. We also uncover phasing information in genes frequently mutated in MM, including DIS3 , HIST1H1E , KRAS , NRAS , and TP53 , phasing 79.4% of 20,705 high-confidence somatic mutations. In some cases, this enabled us to interpret clonal evolution models at higher resolution using pairs of phased somatic mutations. For example, our analysis of one patient suggested that two NRAS hotspot mutations occurred on the same haplotype but were independent events in different subclones. Given sufficient tumor purity and data quality, our framework illustrates how haplotype-aware analysis of somatic mutations in cancer can be beneficial for some cancer cases.