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首页> 外文期刊>Behavior Genetics: An International Journal Devoted to Research in the Inheritance of Behavior in Animals and Man >The National Longitudinal Study of Adolescent to Adult Health (Add Health) Sibling Pairs Genome-Wide Data
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The National Longitudinal Study of Adolescent to Adult Health (Add Health) Sibling Pairs Genome-Wide Data

机译:全国青少年健康状况(添加健康状况)同胞对基因组范围的全国纵向研究

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Here we provide a detailed description of the genome-wide information available on the National Longitudinal Study of Adolescent to Adult Health (Add Health) sibling pair subsample (Harris et al. in Twin Res Hum Genet 16:391-398, 2013). A total of 2,020 samples were genotyped (including duplicates) arising from 1946 Add Health individuals from the sibling pairs subsample. After various steps for quality control (QC) and quality assurance (QA), we have high quality genome-wide data available on 1,888 individuals. In this report, we first highlight the QC and QA steps that were taken to prune the data of poorly performing samples and genetic markers. We further estimate the pairwise biological relationships using genome-wide data and compare those estimates to the assumed relationships in Add Health. Additionally, using genome-wide data from known regional reference populations from Europe, West Africa, North and South America, Japan and China, we estimate the relative genetic ancestry of the respondents. Finally, rather than conducting a traditional cross-sectional genome-wide association study (GWAS) of body mass index (BMI), we opted to utilize the extensive publicly available genome-wide information to conduct a weighted GWAS of longitudinal BMI while accounting for both family and ethnic variation.
机译:在这里,我们提供了有关青少年到成人健康(同伴健康)同胞对子样本的全国纵向研究的可用全基因组信息的详细描述(Harris等人,Twin Res Hum Genet 16:391-398,2013)。共有2020个样本进行了基因分型(包括重复样本),这些样本来自兄弟姐妹对子样本中的1946个Add Health个人。经过质量控制(QC)和质量保证(QA)的各种步骤之后,我们获得了1,888名个体的高质量全基因组数据。在本报告中,我们首先重点介绍为减少表现不佳的样品和遗传标记数据而采取的QC和QA步骤。我们进一步使用全基因组数据估算成对生物学关系,并将这些估算值与Add Health中的假定关系进行比较。此外,使用来自欧洲,西非,北美和南美,日本和中国的已知区域参考人群的全基因组数据,我们估计了受访者的相对遗传血统。最后,我们没有进行体重指数(BMI)的传统横断面全基因组关联研究(GWAS),而是选择利用广泛的公开可用的全基因组信息对纵向BMI进行加权GWAS,同时考虑了两者家庭和种族差异。

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