Cancer Res Treat. 2003 Dec;35(6):533-40. doi: 10.4143/crt.2003.35.6.533.
The cDNA microarray has become a useful tool for observing the expression of thousands of genes simultaneously. However, obtaining good quality microarray data is not easy due to the inherent noise at various stages of the experiment. Therefore, it is essential to understand the source of the variation in the microarray experiment and its size as an initial step of the data analyses.
The total RNA extracted from HT-1080 fibrosarcoma and normal rat tissues were hybridized to the cDNA microarrays with 0.5 K human and 5 K rat genes, respectively. A homotypic reaction and dye swap experiments were used to identify the sources of the variation.
The relative fluorescent intensities of the microarray, if unnormalized, have a large variation, particularly in the lower intensity region. The distribution of the log intensity ratios also exhibit some departure from a band around zero, which is the distribution pattern expected when the majority of genes in the microarray are not regulated. Normalization of the log ratios is usually required as a means of preprocessing the data. We claim that a within-print tip group, an intensity-dependent normalization through a loess fit adjustment will be useful for this purpose, particularly in the initial stages of the microarray experiment.
For proper data analysis, an understanding the source of the variation and preprocessing of data with a suitable normalization method will be important. It is important to have an interactive cooperation between a researcher and a statistician from the early stages of the study design and to the final stages of data analysis.
cDNA 微阵列已成为同时观察数千个基因表达的有用工具。然而，由于实验各个阶段固有的噪声，获得高质量的微阵列数据并不容易。因此，了解微阵列实验中变异的来源及其大小是数据分析的初始步骤是至关重要的。
从 HT-1080 纤维肉瘤和正常大鼠组织中提取总 RNA，分别与包含 0.5 K 个人类和 5 K 个大鼠基因的 cDNA 微阵列进行杂交。使用同型反应和染料交换实验来确定变异的来源。
如果未进行标准化，微阵列的相对荧光强度具有很大的变化，尤其是在低强度区域。对数强度比的分布也表现出一些偏离零的情况，这是当微阵列中大多数基因不受调控时预期的分布模式。通常需要对对数比进行标准化作为数据预处理的一种手段。我们声称，在打印过程中使用组内 tip 进行强度依赖的 loess 拟合调整的归一化将对此有用，特别是在微阵列实验的初始阶段。
为了进行适当的数据分析，了解变异的来源并使用合适的归一化方法预处理数据将是重要的。从研究设计的早期阶段到数据分析的最终阶段，研究人员和统计学家之间进行交互式合作非常重要。
