Burgoon L D, Eckel-Passow J E, Gennings C, Boverhof D R, Burt J W, Fong C J, Zacharewski T R
Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI 48824-1319, USA.
Nucleic Acids Res. 2005 Nov 4;33(19):e172. doi: 10.1093/nar/gni167.
Microarrays represent a powerful technology that provides the ability to simultaneously measure the expression of thousands of genes. However, it is a multi-step process with numerous potential sources of variation that can compromise data analysis and interpretation if left uncontrolled, necessitating the development of quality control protocols to ensure assay consistency and high-quality data. In response to emerging standards, such as the minimum information about a microarray experiment standard, tools are required to ascertain the quality and reproducibility of results within and across studies. To this end, an intralaboratory quality control protocol for two color, spotted microarrays was developed using cDNA microarrays from in vivo and in vitro dose-response and time-course studies. The protocol combines: (i) diagnostic plots monitoring the degree of feature saturation, global feature and background intensities, and feature misalignments with (ii) plots monitoring the intensity distributions within arrays with (iii) a support vector machine (SVM) model. The protocol is applicable to any laboratory with sufficient datasets to establish historical high- and low-quality data.
微阵列代表了一种强大的技术,它能够同时测量数千个基因的表达。然而,这是一个多步骤过程,存在众多潜在的变异来源,如果不加以控制,可能会影响数据分析和解释,因此需要制定质量控制方案以确保检测的一致性和高质量数据。为响应诸如微阵列实验标准的最小信息等新兴标准,需要工具来确定研究内部和研究之间结果的质量和可重复性。为此,利用来自体内和体外剂量反应及时间进程研究的cDNA微阵列,开发了一种用于双色点阵微阵列的实验室内质量控制方案。该方案结合了:(i)监测特征饱和度、全局特征和背景强度以及特征错位程度的诊断图,(ii)监测阵列内强度分布的图,以及(iii)支持向量机(SVM)模型。该方案适用于任何拥有足够数据集以建立历史高质量和低质量数据的实验室。