首页> 外文OA文献 >Using ancestry-informative markers to identify fine structure across 15 populations of European origin.
【2h】

Using ancestry-informative markers to identify fine structure across 15 populations of European origin.

机译:使用祖先信息标记来识别15个欧洲血统群体的精细结构。

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

The Wellcome Trust Case Control Consortium 3 anorexia nervosa genome-wide association scan includes 2907 cases from 15 different populations of European origin genotyped on the Illumina 670K chip. We compared methods for identifying population stratification, and suggest list of markers that may help to counter this problem. It is usual to identify population structure in such studies using only common variants with minor allele frequency (MAF) >5%; we find that this may result in highly informative SNPs being discarded, and suggest that instead all SNPs with MAF >1% may be used. We established informative axes of variation identified via principal component analysis and highlight important features of the genetic structure of diverse European-descent populations, some studied for the first time at this scale. Finally, we investigated the substructure within each of these 15 populations and identified SNPs that help capture hidden stratification. This work can provide information regarding the designing and interpretation of association results in the International Consortia.European Journal of Human Genetics advance online publication, 19 February 2014;
机译:Wellcome Trust病例对照协会3神经性厌食症全基因组关联扫描包括在Illumina 670K芯片上对15种欧洲起源人群进行基因分型的2907例病例。我们比较了识别人群分层的方法,并提出了可能有助于解决这一问题的标记物清单。通常在此类研究中仅使用次要等位基因频率(MAF)> 5%的常见变体来鉴定种群结构;我们发现这可能会导致高信息量的SNP被丢弃,并建议改为可以使用MAF> 1%的所有SNP。我们建立了通过主成分分析确定的信息性变异轴,并突出了欧洲后裔群体遗传结构的重要特征,其中一些是首次在此规模下进行研究。最后,我们调查了这15个种群中每个种群的亚结构,并确定了有助于捕获隐藏分层的SNP。这项工作可以提供有关国际联合会中关联结果的设计和解释的信息。《欧洲人类遗传学杂志》在线提前出版,2014年2月19日;

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号