An evaluation of statistical methods for DNA methylation microarray data analysis

详细信息    查看全文

• 作者：Dongmei Li ; Zidian Xie ; Marc Le Pape ; Timothy Dye
• 关键词：DNA methylation ; Power ; Stability
• 刊名：BMC Bioinformatics
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：16
• 期：1
• 全文大小：3,480 KB
• 刊物主题：Bioinformatics; Microarrays; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Combinatorial Libraries; Algorithms;
• 出版者：BioMed Central
• ISSN：1471-2105

文摘

Background DNA methylation offers an excellent example for elucidating how epigenetic information affects gene expression. β values and M values are commonly used to quantify DNA methylation. Statistical methods applicable to DNA methylation data analysis span a number of approaches such as Wilcoxon rank sum test, t-test, Kolmogorov–Smirnov test, permutation test, empirical Bayes method, and bump hunting method. Nonetheless, selection of an optimal statistical method can be challenging when different methods generate inconsistent results from the same data set.