On differential variability of expression ratios: Improving statistical inference about gene expression changes from microarray data
On differential variability of expression ratios: Improving statistical inference about gene expression changes from microarray data
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DOI：
10.1089/106652701300099074
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发表时间：
2001-01-01
影响因子：
1.7
通讯作者：
Tsui, KW
中科院分区：
文献类型：
--
作者：
Newton, MA;Kendziorski, CM;Tsui, KW
我们考虑从cDNA微阵列数据推断基因表达的折叠变化的问题。标准程序关注的是微阵列上每个点所测荧光强度的比例，但这样做忽略了这样的比例变化不是恒定的事实。基因表达变化的估计是在一个简单的层次模型中推导出来的，该模型考虑了绝对基因表达水平的测量误差和波动。显著的基因表达变化是通过在一个相似的模型中推导后验概率变化来确定的。这些方法通过模拟进行了测试，并应用于大肠杆菌微阵列面板。
We consider the problem of inferring fold changes in gene expression from cDNA microarray data. Standard procedures focus on the ratio of measured fluorescent intensities at each spot on the microarray, but to do so is to ignore the fact that the variation of such ratios is not constant. Estimates of gene expression changes are derived within a simple hierarchical model that accounts for measurement error and fluctuations in absolute gene expression levels. Significant gene expression changes are identified by deriving the posterior odds of change within a similar model. The methods are tested via simulation and are applied to a panel of Escherichia coli microarrays.