Recent Statistical Innovations in Human Genetics

IF 1.2 4区 生物学 Q4 GENETICS & HEREDITY
David J. Balding, Doug Speed
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引用次数: 0

Abstract

We review three areas of human genetics that have been developed in the past few decades, in which statistical innovation has made a crucial contribution with recent important advances and the potential for further rapid progress. The first topic is the development of mathematical models for the genealogy underlying samples of genome-wide genetic data. Coalescent theory emerged in the 1980s, leaped ahead in the past decade and is now burgeoning into new application areas in population, evolutionary and medical genetics. The second is the development of statistical methods for genome-wide association studies which has made great strides over two decades, including exciting recent developments for association testing based on coalescent theory and improved methods for trait prediction. Finally, we review the statistical ideas that helped resolve the controversies surrounding the introduction of forensic DNA profiling in the early 1990s. Big advances in interpretation of the predominant autosomal DNA profiles have set a benchmark for other areas of forensic science, but the statistical assessment of uniparentally inherited profiles (derived from the mitochondrial DNA or the Y chromosome) remains unsatisfactory.

人类遗传学的最新统计创新。
我们回顾了人类遗传学在过去几十年中发展起来的三个领域,其中统计创新在最近的重要进展和进一步快速进展的潜力方面做出了至关重要的贡献。第一个主题是全基因组遗传数据样本的谱系数学模型的发展。聚结理论兴起于20世纪80年代,在过去的十年中突飞猛进,目前正在人口、进化和医学遗传学等新的应用领域蓬勃发展。二是全基因组关联研究的统计方法的发展,在过去的二十年中取得了巨大的进步,包括基于聚结理论的关联测试的令人兴奋的最新发展和改进的性状预测方法。最后,我们回顾了有助于解决20世纪90年代初引入法医DNA分析的争议的统计思想。主要常染色体DNA图谱的解释取得了重大进展,为法医学的其他领域树立了基准,但对单系遗传图谱(来自线粒体DNA或Y染色体)的统计评估仍然令人不满意。
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来源期刊
Annals of Human Genetics
Annals of Human Genetics 生物-遗传学
CiteScore
4.20
自引率
0.00%
发文量
34
审稿时长
3 months
期刊介绍: Annals of Human Genetics publishes material directly concerned with human genetics or the application of scientific principles and techniques to any aspect of human inheritance. Papers that describe work on other species that may be relevant to human genetics will also be considered. Mathematical models should include examples of application to data where possible. Authors are welcome to submit Supporting Information, such as data sets or additional figures or tables, that will not be published in the print edition of the journal, but which will be viewable via the online edition and stored on the website.
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