Multicriteria gene screening for analysis of differential expression with DNA microarrays
Multicriteria gene screening for analysis of differential expression with DNA microarrays
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DOI：
10.1155/s1110865704310036
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发表时间：
2004-01-01
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通讯作者：
Swaroop, A
中科院分区：
文献类型：
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作者：
Hero, AO;Fleury, G;Swaroop, A
本文介绍了一种基于多准则的DNA微阵列实验中差异表达基因识别的统计方法。这些标准是假发现率(FDR)、方差归一化差异表达水平(配对t统计)和最小可接受差异(MAD)。该方法还提供了一组关于真实表达差异的同时FDR可信区间。该分析可以实施为两阶段算法，其中存在仅控制FDR的初始屏幕，然后是控制FDR和MAD两者的第二屏幕。它还可以通过计算和阈值处理满足MAD标准的每个基因的FDRP值集合来实现。我们举例说明了从基因芯片数据的野生型和基因敲除型比较中识别差异表达基因的过程。
This paper introduces a statistical methodology for the identification of differentially expressed genes in DNA microarray experiments based on multiple criteria. These criteria are false discovery rate (FDR), variance-normalized differential expression levels (paired t statistics), and minimum acceptable difference (MAD). The methodology also provides a set of simultaneous FDR confidence intervals on the true expression differences. The analysis can be implemented as a two-stage algorithm in which there is an initial screen that controls only FDR, which is then followed by a second screen which controls both FDR and MAD. It can also be implemented by computing and thresholding the set of FDR P values for each gene that satisfies the MAD criterion. We illustrate the procedure to identify differentially expressed genes from a wild type versus knockout comparison of microarray data.