Iacobas Dumitru A, Massimi Aldo B, Urban Marcia, Iacobas Sanda, Spray David C
Department of Neuroscience, Molecular Biology Core, Kennedy Center, Albert Einstein College of Medicine, Bronx, New York 10461, USA.
J Biomol Tech. 2002 Sep;13(3):143-57.
DNA microarray users face many challenges to obtain accurate results, including complex technical errors, natural variability of biological systems, imperfect reproducibility of reference standards, and difficulties in acquisition and processing of large amounts of data. Therefore, investigators should be aware of potential sources of variability and account for them in the experimental design and execution. This work reports our experience in identifying factors that alter the reliability of the results and in diminishing effects of these factors. We have studied the hybridization reproducibility in cDNA microarray chips, both as absolute values and expression ratios, and the nature and impact of several technical, acquisition, and processing errors. A new experimental strategy is proposed and mathematical algorithms developed that efficiently correct the errors and thereby increase the information obtainable through microarray studies. These algorithms reduced the variability not associated with biological system to less than a quarter of its initial value and have substantially enhanced reliability in experiments on brain and cultured neuroblastoma cells.
DNA微阵列用户在获得准确结果上面临诸多挑战,包括复杂的技术错误、生物系统的自然变异性、参考标准的不完美再现性以及大量数据采集和处理方面的困难。因此,研究人员应意识到变异性的潜在来源,并在实验设计和执行中加以考虑。这项工作报告了我们在识别改变结果可靠性的因素以及减少这些因素影响方面的经验。我们研究了cDNA微阵列芯片中的杂交再现性,包括绝对值和表达比率,以及几种技术、采集和处理错误的性质和影响。提出了一种新的实验策略并开发了数学算法,这些算法能有效校正错误,从而增加通过微阵列研究可获得的信息。这些算法将与生物系统无关的变异性降低到其初始值的四分之一以下,并显著提高了在大脑和培养的神经母细胞瘤细胞实验中的可靠性。