Standardizing global gene expression analysis between laboratories and across platforms
Standardizing global gene expression analysis between laboratories and across platforms
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DOI：
10.1038/nmeth0605-477a
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发表时间：
2005-05-01
期刊：
影响因子：
48
通讯作者：
Zarbl, H
中科院分区：
文献类型：
--
作者：
Bammler, T;Beyer, RP;Zarbl, H
为了促进使用DNA微阵列的多研究人员团队之间的协作研究工作，我们确定了实验室之间以及不同微阵列平台之间的误差来源和数据变异性，以及适应这种变异性的方法。七个实验室生成了RNA表达数据，这些实验室使用12种微阵列平台比较了两种标准RNA样本。所有实验室都至少使用了两种标准微阵列类型（一种是点样的，一种是商业化的）。任何一个实验室内部大多数平台的重现性通常较好，但平台之间以及实验室之间的重现性普遍较差。当针对RNA标记、杂交、微阵列处理、数据采集和数据标准化实施标准化方案时，实验室之间的重现性显著提高。当基于富集的基因本体论（GO）类别所定义的生物学主题进行分析时，重现性最高。这些发现表明，微阵列结果在多个实验室之间是具有可比性的，尤其是当使用共同的平台和一套程序时。
To facilitate collaborative research efforts between multi-investigator teams using DNA microarrays, we identified sources of error and data variability between laboratories and across microarray platforms, and methods to accommodate this variability. RNA expression data were generated in seven laboratories, which compared two standard RNA samples using 12 microarray platforms. At Least two standard microarray types (one spotted, one commercial) were used by all laboratories. Reproducibility for most platforms within any laboratory was typically good, but reproducibility between platforms and across laboratories was generally poor. Reproducibility between laboratories increased markedly when standardized protocols were implemented for RNA labeling, hybridization, microarray processing, data acquisition and data normalization. Reproducibility was highest when analysis was based on biological themes defined by enriched Gene Ontology (GO) categories. These findings indicate that microarray results can be comparable across multiple laboratories, especially when a common platform and set of procedures are used.