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A distribution free summarization method for Affymetrix GeneChip (R) arrays

机译:Affymetrix GeneChip(R)阵列的无分布汇总方法

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Motivation: Affymetrix GeneChip arrays require summarization in order to combine the probe-level intensities into one value representing the expression level of a gene. However, probe intensity measurements are expected to be affected by different levels of non-specific- and cross-hybridization to non-specific transcripts. Here, we present a new summarization technique, the Distribution Free Weighted method (DFW), which uses information about the variability in probe behavior to estimate the extent of non-specific and cross-hybridization for each probe. The contribution of the probe is weighted accordingly during summarization, without making any distributional assumptions for the probe-level data. Results: We compare DFW with several popular summarization methods on spike-in datasets, via both our own calculations and the 'Affycomp II' competition. The results show that DFW outperforms other methods when sensitivity and specificity are considered simultaneously. With the Affycomp spike-in datasets, the area under the receiver operating characteristic curve for DFW is nearly 1.0 (a perfect value), indicating that DFW can identify all differentially expressed genes with a few false positives. The approach used is also computationally faster than most other methods in current use.
机译:动机:Affymetrix GeneChip阵列需要汇总,以便将探针水平的强度组合为一个代表基因表达水平的值。但是,预期探针强度的测量会受到不同水平的非特异性和非特异性转录本杂交的影响。在这里,我们提出了一种新的汇总技术,即分布自由加权方法(DFW),该技术使用有关探针行为可变性的信息来估计每个探针的非特异性杂交交叉程度。在总结过程中,将对探针的贡献进行加权,而无需对探针级别的数据进行任何分布假设。结果:通过我们自己的计算和“ Affycomp II”竞争,我们将DFW与几种常用的尖峰数据集汇总方法进行了比较。结果表明,当同时考虑灵敏度和特异性时,DFW优于其他方法。使用Affycomp插入数据集,DFW的接收器操作特征曲线下的面积接近1.0(理想值),这表明DFW可以识别带有一些假阳性的所有差异表达基因。使用的方法在计算上也比当前使用的大多数其他方法更快。

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