超越种族、民族和祖先的基因组学群体的动态聚类。

IF 2.1 4区 医学 Q3 GENETICS & HEREDITY
Hussein Mohsen, Kim Blenman, Prashant S Emani, Quaid Morris, Jian Carrot-Zhang, Lajos Pusztai
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引用次数: 0

摘要

背景:近几十年来,基因组研究中种族分类的使用稳步减少。虽然仍然包括种族类别的研究在目标和类型上各不相同,但这些类别已经建立在一段历史之上,在这段历史中,种族肤色界线被强制执行和调整,以服务于权力和剥夺公民权的社会和政治制度。对于早期的现代分类系统,数据收集也是相当武断和有限的。固定的、离散的分类限制了人类基因组变异的研究,并破坏了地理尺度上广泛传播的遗传和表型连续体。与此相关,使用广泛的和预定义的分类方案-例如。基于大陆的交叉性状可能会有丢失重要的性状特异性基因组信号的风险。方法:为了解决这些问题,我们引入了一种基于性状特异性位点的基因组变异而不使用一组预定义类别的动态方法来聚类人类基因组学队列。我们在10种癌症类型的全外显子组测序数据集上测试了该方法,并根据可能赋予癌症类型特异性疾病易感性的癌症相关基因的种系变异对其进行了划分。结果:结果显示集群模式,超越离散的大陆为基础的类别跨越癌症类型。基于癌症类型特异性聚类的功能分析还捕获了癌症的基本生物学过程,在功能层面上区分了动态聚类,并识别了被预定义的基于大陆的聚类所忽视的新的潜在驱动因素。结论:通过基于特征的透镜,动态聚类方法揭示了超越预定义分类类别的基因组模式。我们提出,结合不同的数据收集,新的聚类方法有可能绘制更完整的基因组变异肖像,并同时解决其研究的技术和社会方面的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic clustering of genomics cohorts beyond race, ethnicity-and ancestry.

Background: Recent decades have witnessed a steady decrease in the use of race categories in genomic studies. While studies that still include race categories vary in goal and type, these categories already build on a history during which racial color lines have been enforced and adjusted in the service of social and political systems of power and disenfranchisement. For early modern classification systems, data collection was also considerably arbitrary and limited. Fixed, discrete classifications have limited the study of human genomic variation and disrupted widely spread genetic and phenotypic continuums across geographic scales. Relatedly, the use of broad and predefined classification schemes-e.g. continent-based-across traits can risk missing important trait-specific genomic signals.

Methods: To address these issues, we introduce a dynamic approach to clustering human genomics cohorts based on genomic variation in trait-specific loci and without using a set of predefined categories. We tested the approach on whole-exome sequencing datasets in ten cancer types and partitioned them based on germline variants in cancer-relevant genes that could confer cancer type-specific disease predisposition.

Results: Results demonstrate clustering patterns that transcend discrete continent-based categories across cancer types. Functional analysis based on cancer type-specific clusterings also captures the fundamental biological processes underlying cancer, differentiates between dynamic clusters on a functional level, and identifies novel potential drivers overlooked by a predefined continent-based clustering.

Conclusions: Through a trait-based lens, the dynamic clustering approach reveals genomic patterns that transcend predefined classification categories. We propose that coupled with diverse data collection, new clustering approaches have the potential to draw a more complete portrait of genomic variation and to address, in parallel, technical and social aspects of its study.

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来源期刊
BMC Medical Genomics
BMC Medical Genomics 医学-遗传学
CiteScore
3.90
自引率
0.00%
发文量
243
审稿时长
3.5 months
期刊介绍: BMC Medical Genomics is an open access journal publishing original peer-reviewed research articles in all aspects of functional genomics, genome structure, genome-scale population genetics, epigenomics, proteomics, systems analysis, and pharmacogenomics in relation to human health and disease.
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