解决基因组医学中的遗传学差异：一种地理感知算法
Addressing Ancestry Disparities in Genomic Medicine: A Geographic-aware Algorithm
摘要：
随着测序成本的下降，癌症诊断领域出现了一种有前途且负担得起的工具：基因组学。通过使用关联研究，可以识别使患者易患特定癌症的基因组变异，而通过使用肿瘤基因组学，可以表征癌症类型以进行靶向治疗。然而，在精确癌症诊断和治疗计划的这一新领域，一个严重的差距正在迅速出现，这将一些遗传特征良好的人群（主要是欧洲人）与所有其他全球人群分开。在这里，我们讨论了特定人群的遗传协会，这是驱动这种差异的问题，并提出了一种新的解决方案-坐标为基础的本地血统-为帮助解决它。我们展示了我们的增强为基础的方法对全基因组数据来自非洲各地的不同群体，并在此过程中观察信号，可能源于横贯大陆的班图扩张。
英文摘要：
With declining sequencing costs a promising and affordable tool is emerging in cancer diagnostics: genomics. By using association studies, genomic variants that predispose patients to specific cancers can be identified, while by using tumor genomics cancer types can be characterized for targeted treatment. However, a severe disparity is rapidly emerging in this new area of precision cancer diagnosis and treatment planning, one which separates a few genetically well-characterized populations (predominantly European) from all other global populations. Here we discuss the problem of population-specific genetic associations, which is driving this disparity, and present a novel solution--coordinate-based local ancestry--for helping to address it. We demonstrate our boosting-based method on whole genome data from divergent groups across Africa and in the process observe signals that may stem from the transcontinental Bantu-expansion.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
