Numerical Deconvolution of cDNA Microarray Signal: Simulation Study
Numerical Deconvolution of cDNA Microarray Signal: Simulation Study
复制标题
cDNA 微阵列信号的数值解卷积：模拟研究
DOI：
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发表时间：
2004
影响因子：
5.2
通讯作者：
John A. Milner
中科院分区：
文献类型：
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作者：
S. Rosenfeld;Thomas Wang;Y. Kim;John A. Milner
翻译后摘要：模拟的cDNA微阵列实验的计算模型已经创建。模拟允许人们预见重复实验的统计特性，而无需实际执行它们。我们引入了一个新概念，即所谓的生物重量，它允许在微阵列实验中协调生物学和统计学显着性的相互冲突的含义。结果表明，对于小样本量，与基于t检验的标准方法相比，生物重量是微阵列数据中存在信号的更有力的标准。微阵列和定量PCR数据的联合模拟表明，通过使用生物重量回收的基因比通过t检验技术获得的基因有更好的机会被PCR确认。我们还采用极值的考虑，以获得合理的截断水平的假设检验。
Abstract: A computational model for simulation of the cDNA microarray experiments has been created. The simulation allows one to foresee the statistical properties of replicated experiments without actually performing them. We introduce a new concept, the so‐called bio‐weight, which allows for reconciliation between conflicting meanings of biological and statistical significance in microarray experiments. It is shown that, for a small sample size, the bio‐weight is a more powerful criterion of the presence of a signal in microarray data as compared to the standard approach based on t test. Joint simulation of microarray and quantitative PCR data shows that the genes recovered by using the bio‐weight have better chances to be confirmed by PCR than those obtained by the t test technique. We also employ extreme value considerations to derive plausible cutoff levels for hypothesis testing.