https://scholars.lib.ntu.edu.tw/handle/123456789/521783
標題: | Detecting differentially expressed genes in heterogeneous diseases using half Student's t-test | 作者: | Hsu C.-L. WEN-CHUNG LEE |
公開日期: | 2010 | 卷: | 39 | 期: | 6 | 起(迄)頁: | 1597-1604 | 來源出版物: | International Journal of Epidemiology | 摘要: | Background: Microarray technology provides information about hundreds and thousands of gene-expression data in a single experiment. To search for disease-related genes, researchers test for those genes that are differentially expressed between the case subjects and the control subjects. Methods: The authors propose a new test, the 'half Student's t-test', specifically for detecting differentially expressed genes in heterogeneous diseases. Monte-Carlo simulation shows that the test maintains the nominal α level quite well for both normal and non-normal distributions. Power of the half Student's t is higher than that of the conventional 'pooled' Student's t when there is heterogeneity in the disease under study. The power gain by using the half Student's t can reach ~10% when the standard deviation of the case group is 50% larger than that of the control group. Results: Application to a colon cancer data reveals that when the false discovery rate (FDR) is controlled at 0.05, the half Student's t can detect 344 differentially expressed genes, whereas the pooled Student's t can detect only 65 genes. Or alternatively, if only 50 genes are to be selected, the FDR for the pooled Student's t has to be set at 0.0320 (false positive rate of ~3%), but for the half Student's t, it can be at as low as 0.0001 (false positive rate of about one per ten thousands). Conclusions: The half Student's t-test is to be recommended for the detection of differentially expressed genes in heterogeneous diseases. Published by Oxford University Press on behalf of the International Epidemiological Association ? The Author 2010; all rights reserved. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-78649790236&doi=10.1093%2fije%2fdyq093&partnerID=40&md5=705a0f3d702707a080d58a5b9936edb6 https://scholars.lib.ntu.edu.tw/handle/123456789/521783 |
ISSN: | 0300-5771 | DOI: | 10.1093/ije/dyq093 | SDG/關鍵字: | cancer; detection method; disease treatment; epidemiology; gene expression; heterogeneity; Monte Carlo analysis; article; colon cancer; controlled study; gene expression; gene identification; genetic association; Monte Carlo method; priority journal; Student t test; Colonic Neoplasms; Computer Simulation; Gene Expression; Humans; Models, Statistical; Monte Carlo Method; Statistics, Nonparametric |
顯示於: | 流行病學與預防醫學研究所 |
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