Department of Mathematics and Statistics, University of South Alabama, Mobile, AL 36688, USA.
Bioinformatics. 2010 Jan 15;26(2):228-34. doi: 10.1093/bioinformatics/btp655. Epub 2009 Nov 23.
MicroRNA (miRNA) is a set of newly discovered non-coding small RNA molecules. Its significant effects have contributed to a number of critical biological events including cell proliferation, apoptosis development, as well as tumorigenesis. High-dimensional genomic discovery platforms (e.g. microarray) have been employed to evaluate the important roles of miRNAs by analyzing their expression profiling. However, because of the small total number of miRNAs and the absence of well-known endogenous controls, the traditional normalization methods for messenger RNA (mRNA) profiling analysis could not offer a suitable solution for miRNA analysis. The need for the establishment of new adaptive methods has come to the forefront.
Locked nucleic acid (LNA)-based miRNA array was employed to profile miRNAs using colorectal cancer cell lines under different treatments. The expression pattern of overall miRNA profiling was pre-evaluated by a panel of miRNAs using Taqman-based quantitative real-time polymerase chain reaction (qRT-PCR) miRNA assays. A logistic regression model was built based on qRT-PCR results and then applied to the normalization of miRNA array data. The expression levels of 20 additional miRNAs selected from the normalized list were post-validated. Compared with other popularly used normalization methods, the logistic regression model efficiently calibrates the variance across arrays and improves miRNA microarray discovery accuracy.
Datasets and R package are available at http://gauss.usouthal.edu/publ/logit/.
MicroRNA（miRNA）是一组新发现的非编码小分子 RNA。其重要作用促成了许多关键的生物学事件，包括细胞增殖、凋亡发展以及肿瘤发生。高维基因组发现平台（例如微阵列）已被用于通过分析其表达谱来评估 miRNA 的重要作用。然而，由于 miRNA 的总数较少，并且缺乏众所周知的内源性对照，传统的信使 RNA（mRNA）分析的标准化方法无法为 miRNA 分析提供合适的解决方案。建立新的适应性方法的需求已经迫在眉睫。
使用基于锁核酸（LNA）的 miRNA 阵列在不同处理下对结直肠癌细胞系中的 miRNA 进行了分析。使用 Taqman 基于定量实时聚合酶链反应（qRT-PCR）miRNA 测定法，通过一组 miRNA 对整体 miRNA 分析的表达模式进行了预评估。基于 qRT-PCR 结果构建了逻辑回归模型，并将其应用于 miRNA 阵列数据的标准化。从标准化列表中选择的另外 20 个 miRNA 的表达水平进行了后续验证。与其他常用的标准化方法相比，逻辑回归模型有效地校准了各个阵列之间的方差，提高了 miRNA 微阵列发现的准确性。
数据集和 R 包可在 http://gauss.usouthal.edu/publ/logit/ 上获得。
