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三十年方法论工作坊笔记。

Notes on Three Decades of Methodology Workshops.

机构信息

Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, PO Box 980033, Richmond, VA, 23298-0033, USA.

Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA.

出版信息

Behav Genet. 2021 May;51(3):170-180. doi: 10.1007/s10519-021-10049-9. Epub 2021 Feb 14.

DOI:10.1007/s10519-021-10049-9
PMID:33585974
Abstract

Since 1987, a group of behavior geneticists have been teaching an annual methodology workshop on how to use state-of-the-art methods to analyze genetically informative data. In the early years, the focus was on analyzing twin and family data, using information of their known genetic relatedness to infer the role of genetic and environmental factors on phenotypic variation. With the rapid evolution of genotyping and sequencing technology and availability of measured genetic data, new methods to detect genetic variants associated with human traits were developed and became the focus of workshop teaching in alternate years. Over the years, many of the methodological advances in the field of statistical genetics have been direct outgrowths of the workshop, as evidence by the software and methodological publications authored by workshop faculty. We provide data and demographics of workshop attendees and evaluate the impact of the methodology workshops on scientific output in the field by evaluating the number of papers applying specific statistical genetic methodologies authored by individuals who have attended workshops.

摘要

自 1987 年以来,一群行为遗传学家一直在教授年度方法论研讨会,介绍如何使用最先进的方法来分析具有遗传信息的数据。在早期,重点是分析双胞胎和家庭数据,利用他们已知的遗传相关性的信息来推断遗传和环境因素对表型变异的作用。随着基因分型和测序技术的快速发展以及可测量遗传数据的可用性,开发了检测与人类特征相关的遗传变异的新方法,并成为研讨会隔年教学的重点。多年来,统计遗传学领域的许多方法学进展直接源自于研讨会,这一点可以从研讨会教师编写的软件和方法学出版物中得到证明。我们提供了研讨会参与者的数据和人口统计学信息,并通过评估参加过研讨会的个人撰写的应用特定统计遗传方法的论文数量,来评估方法论研讨会对该领域科学产出的影响。

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本文引用的文献

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Using Multimodel Inference/Model Averaging to Model Causes of Covariation Between Variables in Twins.使用多模型推断/模型平均来模拟双胞胎变量间协变的原因。
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Genomic structural equation modelling provides insights into the multivariate genetic architecture of complex traits.基因组结构方程模型为复杂性状的多变量遗传结构提供了深入的了解。
Nat Hum Behav. 2019 May;3(5):513-525. doi: 10.1038/s41562-019-0566-x. Epub 2019 Apr 8.
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Type I Error Rates and Parameter Bias in Multivariate Behavioral Genetic Models.
多变量行为遗传模型中的I型错误率和参数偏差
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Extending Causality Tests with Genetic Instruments: An Integration of Mendelian Randomization with the Classical Twin Design.利用遗传工具扩展因果关系检验:孟德尔随机化与经典双生子设计的整合。
Behav Genet. 2018 Jul;48(4):337-349. doi: 10.1007/s10519-018-9904-4. Epub 2018 Jun 7.
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Functional mapping and annotation of genetic associations with FUMA.使用 FUMA 进行遗传关联的功能映射和注释。
Nat Commun. 2017 Nov 28;8(1):1826. doi: 10.1038/s41467-017-01261-5.
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An Extended Twin-Pedigree Study of Neuroticism in the Netherlands Twin Register.荷兰双胞胎登记处神经质的扩展双胞胎谱系研究。
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Attention Deficit Hyperactivity Disorder Symptoms and Low Educational Achievement: Evidence Supporting A Causal Hypothesis.注意力缺陷多动障碍症状与低学业成就:支持因果假设的证据
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Behav Genet. 2016 Sep;46(5):627-648. doi: 10.1007/s10519-016-9797-z. Epub 2016 Jun 8.