优化计算祖先推断用于癌症细胞系的优化
Matthew S Chang1, Katherine A Martinez1, Chayil C Lattimore1
1Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL 32610, United States.
Biology methods & protocols
|June 30, 2025
概括
我们开发了一个计算工作流程,从癌症细胞系序列数据推断出基因祖先. 全基因组测序 (WGS) 数据提供了比RNA测序 (RNA-seq) 数据更准确的祖先估计.
科学领域:
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 癌症研究 癌症研究
背景情况:
- 癌症细胞系对于癌症健康差异研究至关重要.
- 现有的祖先推断方法主要使用微阵列数据,缺乏对数据测序的指导.
- 准确的遗传祖先推断对于理解癌症差异至关重要.
研究的目的:
- 描述一种计算工作流程,用于从癌症细胞系的全基因组测序 (WGS) 和RNA测序 (RNA-seq) 数据中推断基因祖先.
- 优化SNP过和集群,以改善祖先推断.
- 为了比较WGS与RNA-seq对遗传祖先估计的有效性.
主要方法:
- 从四个头癌细胞系生成了WGS和RNA-seq数据集.
- 利用Illumina DRAGEN管道进行变异调用和基因型归算.
- 与1000个基因组项目 (1KGP) 整合数据,使用PLINK过SNP,并使用ADMIXTURE推断祖先.
- 优化了SNP过的参数 (100kb窗口,r2 0.8) 并使用291个祖先信息标记器来改进集群.
主要成果:
- 工作流成功地从WGS和RNA-seq数据中推断出遗传祖先.
- 优化过和聚类可以提高祖先估计的准确性.
- 与RNA-seq.相比,全基因组测序 (WGS) 数据集在超级人口聚类和遗传祖先比例估计方面表现优异.
- 从WGS数据推断的祖先与测试细胞系的自我识别种族/种族 (SIRE) 保持一致.
结论:
- 开发的工作流提供了一种强大的方法,可以从癌症细胞系序列数据中推断基因祖先.
- 建议采用全基因组测序 (WGS) 而不是RNA测序 (RNA-seq),以便在癌症细胞系中更准确地推断遗传祖先.
- 这种方法可以通过为细胞系模型提供精确的祖先信息来增强癌症健康差异研究.
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