Can one compare Beta values of methylation, such as those found at TCGA, using t-Test? This qutation is from from: An evaluation of statistical methods for DNA methylation microarray data analysis, BMC Bioinformatics. 2015; 16: 217.
Currently available methylation differential analysis methods implemented in Bioconductor/R include several approaches such as Wilcoxon rank sum test (used in methyAnalysis package), t-test (used in methyAnalysis, CpGAssoc, RnBeads, and IMA package), Kolmogorov-Smirnov Tests (although not implemented in packages, but used by some investigators ), permutation test (used in CpGAssoc package), empirical Bayes method (used in RnBeads, IMA and minfi package), and bump hunting method (used in bumphunter and minfi package).
What I mean is, if beta values of condition a are c(0.5,0.5,0.5,0.50001) are these considered different from c(0.51,0.51, 0.51, 0.51)?
> t.test( c(0.5,0.5,0.5,0.50001), c(0.51,0.51, 0.51, 0.51))$p.value  3.44839e-11
but we know that beta value of 0.5 itself means data are heterogeneous??