a method to address differential bias in genotyping in large-scale association studies基因分型方法来解决微分偏见在大规模的关联研究.pdfVIP

a method to address differential bias in genotyping in large-scale association studies基因分型方法来解决微分偏见在大规模的关联研究.pdf

  1. 1、本文档共9页,可阅读全部内容。
  2. 2、有哪些信誉好的足球投注网站(book118)网站文档一经付费(服务费),不意味着购买了该文档的版权,仅供个人/单位学习、研究之用,不得用于商业用途,未经授权,严禁复制、发行、汇编、翻译或者网络传播等,侵权必究。
  3. 3、本站所有内容均由合作方或网友上传,本站不对文档的完整性、权威性及其观点立场正确性做任何保证或承诺!文档内容仅供研究参考,付费前请自行鉴别。如您付费,意味着您自己接受本站规则且自行承担风险,本站不退款、不进行额外附加服务;查看《如何避免下载的几个坑》。如果您已付费下载过本站文档,您可以点击 这里二次下载
  4. 4、如文档侵犯商业秘密、侵犯著作权、侵犯人身权等,请点击“版权申诉”(推荐),也可以打举报电话:400-050-0827(电话支持时间:9:00-18:30)。
  5. 5、该文档为VIP文档,如果想要下载,成为VIP会员后,下载免费。
  6. 6、成为VIP后,下载本文档将扣除1次下载权益。下载后,不支持退款、换文档。如有疑问请联系我们
  7. 7、成为VIP后,您将拥有八大权益,权益包括:VIP文档下载权益、阅读免打扰、文档格式转换、高级专利检索、专属身份标志、高级客服、多端互通、版权登记。
  8. 8、VIP文档为合作方或网友上传,每下载1次, 网站将根据用户上传文档的质量评分、类型等,对文档贡献者给予高额补贴、流量扶持。如果你也想贡献VIP文档。上传文档
查看更多
a method to address differential bias in genotyping in large-scale association studies基因分型方法来解决微分偏见在大规模的关联研究

A Method to Address Differential Bias in Genotyping in Large-Scale Association Studies * Vincent Plagnol , Jason. D. Cooper, John A. Todd, David G. Clayton Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, United Kingdom In a previous paper we have shown that, when DNA samples for cases and controls are prepared in different laboratories prior to high-throughput genotyping, scoring inaccuracies can lead to differential misclassification and, consequently, to increased false-positive rates. Different DNA sourcing is often unavoidable in large-scale disease association studies of multiple case and control sets. Here, we describe methodological improvements to minimise such biases. These fall into two categories: improvements to the basic clustering methods for identifying genotypes from fluorescence intensities, and use of ‘‘fuzzy’’ calls in association tests in order to make appropriate allowance for call uncertainty. We find that the main improvement is a modification of the calling algorithm that links the clustering of cases and controls while allowing for different DNA sourcing. We also find that, in the presence of different DNA sourcing, biases associated with missing data can increase the false-positive rate. Therefore, we propose the use of ‘‘fuzzy’’ calls to deal with uncertain genotypes that would otherwise be labeled as missing. Citation: Plagnol V, Cooper JD, Todd JA, Clayton DG (2007) A method to address differential bias in genotyping in large-scale association studies. PLoS Genet 3(5): e74. doi:10. 1371/journal.pgen.0030074 Introduction approach is that it can generate a differential bias in

您可能关注的文档

文档评论(0)

qianqiana + 关注
实名认证
文档贡献者

该用户很懒,什么也没介绍

版权声明书
用户编号:5132241303000003

1亿VIP精品文档

相关文档