Chen Dung-Tsa
Biostatistics and Bioinformatics Unit, University of Alabama at Birmingham, Birmingham, AL 35294, USA.
J Biopharm Stat. 2004 Aug;14(3):591-606. doi: 10.1081/BIP-200025651.
In studies of quality control of oligonucleotide array data, one objective is to screen out ineligible arrays. Incomparable arrays (one type of ineligible arrays) arise as the experimental factors are poorly controlled. Due to the high volume of data in gene arrays, examination of array comparability requires special treatments to reduce data dimension without distortion. This paper proposes a graphical approach to address these issues. The proposed approach uses percentile methods to group data, and applies the 2D image plot to display the grouped data. Moreover, an invariant band is employed to quantify degrees of array comparability. We use two publicly available oligonucleotide array datasets from Affymetrix GeneChip System for evaluation. The results demonstrate the utility of our approach to examine data quality and also as an exploratory tool to verify differentially expressed genes selected by vigorous statistical methods.
在寡核苷酸阵列数据的质量控制研究中,一个目标是筛选出不合格的阵列。由于实验因素控制不佳,会出现不可比阵列(一种不合格阵列)。由于基因阵列中的数据量很大,检查阵列可比性需要特殊处理以在不扭曲的情况下降低数据维度。本文提出了一种图形方法来解决这些问题。所提出的方法使用百分位数方法对数据进行分组,并应用二维图像图来显示分组后的数据。此外,采用不变带来量化阵列可比性的程度。我们使用来自Affymetrix GeneChip系统的两个公开可用的寡核苷酸阵列数据集进行评估。结果证明了我们的方法在检查数据质量方面的效用,以及作为一种探索性工具来验证通过严格统计方法选择的差异表达基因的效用。