| 题名: | Modified Significance Analysis of Microarrays in Heterogeneous Diseases |
| 作者: | Tzeng, IS (Tzeng, I-Shiang) |
| 贡献者: | 運健系 |
| 关键词: | gene expression
heterogeneous data
significance analysis of microarrays |
| 日期: | 2021-02 |
| 上传时间: | 2021-04-19 10:21:22 (UTC+8) |
| 摘要: | Significance analysis of microarrays (SAM) provides researchers with a non-parametric score for each gene based on repeated measurements. However, it may lose certain power in general statistical tests to correctly detect differentially expressed genes (DEGs) which violate homogeneity. Monte Carlo simulation shows that the "half SAM score" can maintain type I error rates of about 0.05 based on assumptions of normal and non-normal distributions. The author found 265 DEGs using the half SAM scoring, more than the 119 DEGs detected by SAM, with the false discovery rate controlled at 0.05. In conclusion, the author recommends the half SAM scoring method to detect DEGs in data that show heterogeneity. |
| 關聯: | JOURNAL OF PERSONALIZED MEDICINE卷冊: 11 期: 2 文獻號碼: 62 |
| 显示于类别: | [運動與健康促進學系] 期刊論文
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