論文

査読有り
2008年5月

Sample-size properties of a case-control association analysis of multistage SNP studies for identifying disease susceptibility genes

JOURNAL OF HUMAN GENETICS
  • Nobutaka Kitamura
  • ,
  • Kouhei Akazawa
  • ,
  • Shin-ichi Toyabe
  • ,
  • Akinori Miyashita
  • ,
  • Ryozo Kuwano
  • ,
  • Junichiro Nakamura

53
5
開始ページ
390
終了ページ
400
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1007/s10038-008-0258-2
出版者・発行元
NATURE PUBLISHING GROUP

A two-stage association study is the most commonly used method to efficiently identify disease susceptibility genes. However, some recent single nucleotide polymorphism (SNP) studies recently utilized three-stage designs. The purpose of this study was to investigate the practical properties of statistical powers and positive predictive values (PPVs) of replication-based analysis (RBA) and the joint analysis (JA) in multistage designs. For this purpose, a program for multistage designs was developed to calculate these performance indicators under various conditions of the number of samples, alleles of candidates, alleles remaining in the final stage, and genotypings. The results showed that the powers and PPVs of RBA and JA in three-stage designs were higher than those in two-stage designs in the range of a smaller proportion of sample size than 0.5 at the first stage. This tendency was more remarkable in JA. In conclusion, researchers who perform SNP studies for identifying disease susceptibility genes need to take account of three-stage case-control association studies, corresponding to study conditions such as the total numbers of samples, alleles, and genotypings. Furthermore, the program developed in this study is useful for estimating powers and PPVs in planning multistage association studies.

リンク情報
DOI
https://doi.org/10.1007/s10038-008-0258-2
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/18288444
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000255742600003&DestApp=WOS_CPL
ID情報
  • DOI : 10.1007/s10038-008-0258-2
  • ISSN : 1434-5161
  • PubMed ID : 18288444
  • Web of Science ID : WOS:000255742600003

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