[1]王婷),曾平)#,黄水平),等.微阵列数据分析和错误发现率*[J].郑州大学学报(医学版),2013,(01):59.
 WANG Ting,ZENG Ping,HUANG Shuiping,et al.Microarray data analysis and false discovery rate[J].JOURNAL OF ZHENGZHOU UNIVERSITY(MEDICAL SCIENCES),2013,(01):59.
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微阵列数据分析和错误发现率*
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《郑州大学学报(医学版)》[ISSN:1671-6825/CN:41-1340/R]

卷:
期数:
2013年01期
页码:
59
栏目:
论著
出版日期:
2013-01-20

文章信息/Info

Title:
Microarray data analysis and false discovery rate
作者:
王婷1)曾平12)#黄水平1)赵华硕1)
1)徐州医学院公共卫生学院流行病学与卫生统计学教研室 徐州 221002 2)南京医科大学公共卫生学院流行病学与卫生统计学教研室 南京 210029
Author(s):
WANG Ting1)ZENG Ping12)HUANG Shuiping1)ZHAO Huashuo1)
1)Department of Epidemiology and Health Statistics,School of Public Health,Xuzhou Medical College,Xuzhou 221002 2)Department of Epidemiology and Health Statistics,School of Public Health,Nanjing Medical University,Nanjing 210029
关键词:
微阵列数据多重假设检验错误发现率控制和估计前列腺癌
Keywords:
microarray datamultiple hypotheses testingfalse discovery ratecontrol and estimationprostate cancer
分类号:
R195.1
摘要:
目的:介绍微阵列数据的差异表达分析和基于错误发现率的多重假设检验。方法:通过t检验对一个关于前列腺癌的微阵列数据进行基因差异表达分析,采用BH程序进行错误发现率的控制和经验估计。结果:当错误发现率为0.05时通过BH程序得到21个差异表达基因;当以|t|≥3作为拒绝域时,得到105个基因,对应的错误发现率估计值为0.20。结论:相对传统的总体错误率,错误发现率更加适合于微阵列这种高维数据多重比较的错误控制;而且能同时控制或估计错误发现率。
Abstract:
Aim:To introduce the analysis of differential expression of microarray data and the multiple hypotheses testing based on the false discovery rate(FDR).Methods:The t test was used for the analysis of differentially expressed genes concerning prostate cancer microarray data.FDR controlled with the procedure of Benjamini and Hochberg(BH)was empirically estimated.Results:A total of 21 differentially expressed genes were obtained by the BH procedure with the FDR of 005;and 105 genes were obtained with an estimated FDR of 0.20 if the rejection region was |t|≥3.Conclusion:FDR is more appropriate for highdimensional microarray data in multiple comparisons than family wise error rate;we can control and estimate the FDR at the same time.

参考文献/References:

[1]Johnstone IM,Titterington DM.Statistical challenges of highdimensional data[J].Philos Transact A Math Phys Eng Sci,2009,367(1906):4237
[2]Bretz F,Hothorn T,Westfall P.Multiple comparisons using R[M].London:Chapman & Hall,2010:11
[3]Benjamini Y,Hochberg Y.Controlling the false discovery rate:A practical and powerful approach to multiple testing[J].J Royal Statist Soc:Series B,1995,57(1):28
[4]Efron B.Largescale inference:empirical Bayes methods for estimation,testing,and prediction[M].New York:Cambridge University Press,2010:46
[5]Singh D,Febbo PG,Ross K,et al.Gene expression correlates of clinical prostate cancer behavior[J].Cancer Cell,2002,1(2):203
[6]曾平,王婷.贝叶斯错误发现率[J].山东大学学报:医学版,2012,50(3):120
[7]王婷,曾平,黄水平,等.错误发现率及其扩展和应用[J].重庆医科大学学报,2011,36(12):38
[8]王婷,曾平,黄水平,等.错误发现率的经验估计和应用[J].郑州大学学报:医学版,2012,47(5):636
[9]R Development Core Team.R:A language and environment for statistical computing[EB/OL].R Foundation for Statistical Computing,Vienna,Austria,2007.URL http://www.Rproject.org.
[10]荀鹏程,赵杨,易洪刚,等.Permutation Test在假设检验中的应用[J].数理统计与管理,2006,25(5):616
[11]Hastie T,Tibshirani R,Friedman J.The elements of statistical learning:data mining,inference,and prediction,second edition[M].New York:SpringerVerlag,2009.
[12]Benjamini Y.Discovering the false discovery rate[J].J Royal Statist Soc:Series B,2010,72(4):405

相似文献/References:

[1]王婷),曾平)#,黄水平),等.错误发现率的经验估计和应用*[J].郑州大学学报(医学版),2012,(05):636.
 WANG Ting),ZENG Ping),HUANG Shuiping),et al.Empirical estimation and application of false discovery rate[J].JOURNAL OF ZHENGZHOU UNIVERSITY(MEDICAL SCIENCES),2012,(01):636.

备注/Memo

备注/Memo:
*江苏省教育厅高校哲学社会科学研究基金资助项目2010SJB790037;徐州医学院公共卫生学院科研课题资助项目201107,201115 #通讯作者,男,1982年7月生,硕士,助教,研究方向:高纬数据分析和贝叶斯统计,Email:zpstat@xzmc.edu.cn
更新日期/Last Update: 2013-04-19