Effect of various normalization methods on Applied Biosystems expression array system data.
Effect of various normalization methods on Applied Biosystems expression array system data.
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各种归一化方法对应用生物系统表达阵列系统数据的影响。
DOI：
10.1186/1471-2105-7-533
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发表时间：
2006-12-15
影响因子：
3
通讯作者：
Samaha, Raymond R.
中科院分区：
文献类型：
--
作者：
Barbacioru, Catalin C.;Wang, Yulei;Canales, Roger D.;Sun, Yongming A.;Keys, David N.;Chan, Frances;Poulter, Karen A.;Samaha, Raymond R.
DNA 微阵列技术为在基因组规模上表征基因表达提供了强大的工具。虽然该技术已广泛应用于基于发现的医学和基础生物学研究，但其在临床实践和监管决策中的直接应用受到质疑。在临床实验室和监管领域常规使用微阵列之前，必须认真解决一些关键问题，包括微阵列分析和结果的可重复性、可靠性、兼容性和标准化。在这项研究中，我们研究了应用生物系统公司人类基因组调查微阵列的一些问题。我们使用 Applied Biosystems 人类基因组调查微阵列分析了两个样本的基因表达谱：大脑和通用人类参考 (UHR)，这是来自 10 个癌细胞系的 RNA 混合物。根据制造商的标准方案，在三个不同地点对相同的总 RNA 样品进行五次技术重复。使用五种不同的方法（分位数、中位数、尺度、VSN 和循环黄土）对每个位点内的 AB 微阵列数据进行标准化。选择了 1,000 个基因表达水平动态范围广泛的基因进行实时 PCR 验证。使用TaqMan®检测数据集作为参考集，评估五种归一化方法的性能，重点关注以下标准：（1）表达检测的灵敏度和重现性； (2) 倍数变化与实时PCR数据的相关性； (3)差异表达检测的灵敏度和特异性； (4)差异表达基因列表的重现性。我们的结果表明这些标准化方法之间具有高度的一致性。无论是否询问信号、检测、变异、倍数变化测量和再现性，这都是事实。此外，我们使用 TaqMan® 检测作为参考，为检测范围内的各种标准化方法生成 TPR 和 FDR 图。在检测差异表达基因时，对 TP 和 FP 率几乎没有影响。此外，观察到各种归一化方法对分析的统计方法几乎没有影响，这表明当前在该领域使用的分析方法具有一定的鲁棒性，特别是与Applied Biosystems基因表达系统结合使用时。
DNA microarray technology provides a powerful tool for characterizing gene expression on a genome scale. While the technology has been widely used in discovery-based medical and basic biological research, its direct application in clinical practice and regulatory decision-making has been questioned. A few key issues, including the reproducibility, reliability, compatibility and standardization of microarray analysis and results, must be critically addressed before any routine usage of microarrays in clinical laboratory and regulated areas can occur. In this study we investigate some of these issues for the Applied Biosystems Human Genome Survey Microarrays. We analyzed the gene expression profiles of two samples: brain and universal human reference (UHR), a mixture of RNAs from 10 cancer cell lines, using the Applied Biosystems Human Genome Survey Microarrays. Five technical replicates in three different sites were performed on the same total RNA samples according to manufacturer's standard protocols. Five different methods, quantile, median, scale, VSN and cyclic loess were used to normalize AB microarray data within each site. 1,000 genes spanning a wide dynamic range in gene expression levels were selected for real-time PCR validation. Using the TaqMan® assays data set as the reference set, the performance of the five normalization methods was evaluated focusing on the following criteria: (1) Sensitivity and reproducibility in detection of expression; (2) Fold change correlation with real-time PCR data; (3) Sensitivity and specificity in detection of differential expression; (4) Reproducibility of differentially expressed gene lists. Our results showed a high level of concordance between these normalization methods. This is true, regardless of whether signal, detection, variation, fold change measurements and reproducibility were interrogated. Furthermore, we used TaqMan® assays as a reference, to generate TPR and FDR plots for the various normalization methods across the assay range. Little impact is observed on the TP and FP rates in detection of differentially expressed genes. Additionally, little effect was observed by the various normalization methods on the statistical approaches analyzed which indicates a certain robustness of the analysis methods currently in use in the field, particularly when used in conjunction with the Applied Biosystems Gene Expression System.
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DOI：
10.1073/pnas.091062498
发表时间：
2001-04-24
影响因子：
11.1
作者：
Tusher, VG;Tibshirani, R;Chu, G
通讯作者：
Chu, G
影响因子：
7
作者：
Gibson, UEM;Heid, CA;Williams, PM
通讯作者：
Williams, PM
影响因子：
7
作者：
Heid, CA;Stevens, J;Williams, PM
通讯作者：
Williams, PM
影响因子：
46.9
作者：
Canales, Roger D.;Luo, Yuling;Goodsaid, Federico M.
通讯作者：
Goodsaid, Federico M.
影响因子：
4.4
作者：
Wang, Yulei;Barbacioru, Catalin;Hyland, Fiona;Xiao, Wenming;Hunkapiller, Kathryn L;Blake, Julie;Chan, Frances;Gonzalez, Carolyn;Zhang, Lu;Samaha, Raymond R
通讯作者：
Samaha, Raymond R