Apparently low reproducibility of true differential expression discoveries in microarray studies
Apparently low reproducibility of true differential expression discoveries in microarray studies
复制标题
微阵列研究中真实差异表达发现的再现性明显较低
DOI：
10.1093/bioinformatics/btn365
复制
发表时间：
2008-09-15
期刊：
影响因子：
5.8
通讯作者：
Li, Xia
中科院分区：
文献类型：
--
作者：
Zhang, Min;Yao, Chen;Li, Xia
动机
从针对同一疾病的不同微阵列研究中检测到的差异表达基因（DEG）列表通常高度不一致。即使在使用相同样品的技术重复测试中，DEG 检测的重现性仍然很低。人们通常认为当前的小型微阵列研究将在很大程度上引入错误的发现。
结果
基于统计模型，我们表明，即使在使用相同样本的技术重复测试中，在存在小的测量变化的情况下，所选的 DEG 列表也很可能非常不一致。因此，从当前技术重复测试中DEG检测的明显低再现性并不表明微阵列技术的质量低。我们还证明，真实癌症数据中存在的异质生物学变异将进一步降低 DEG 检测的整体再现性。然而，在模拟数据和真实数据的小子样本中，每个 DEG 列表的实际错误发现率 (FDR) 往往较低，这表明每个单独确定的列表可能主要包含真实的 DEG。需要新的指标来评估以相关分子变化为特征的发现的可重复性，而不是简单地计算来自复杂疾病的不同研究的发现列表的重叠。补充信息：补充数据可在生物信息学在线获取。
MOTIVATION
Differentially expressed gene (DEG) lists detected from different microarray studies for a same disease are often highly inconsistent. Even in technical replicate tests using identical samples, DEG detection still shows very low reproducibility. It is often believed that current small microarray studies will largely introduce false discoveries.
RESULTS
Based on a statistical model, we show that even in technical replicate tests using identical samples, it is highly likely that the selected DEG lists will be very inconsistent in the presence of small measurement variations. Therefore, the apparently low reproducibility of DEG detection from current technical replicate tests does not indicate low quality of microarray technology. We also demonstrate that heterogeneous biological variations existing in real cancer data will further reduce the overall reproducibility of DEG detection. Nevertheless, in small subsamples from both simulated and real data, the actual false discovery rate (FDR) for each DEG list tends to be low, suggesting that each separately determined list may comprise mostly true DEGs. Rather than simply counting the overlaps of the discovery lists from different studies for a complex disease, novel metrics are needed for evaluating the reproducibility of discoveries characterized with correlated molecular changes. Supplementaty information: Supplementary data are available at Bioinformatics online.