Table 1.

Bioinformatic tools and pipelines for analyzing methylation data.

Name	Platfor	GUI	Data Types	QC	Preprocess	Cell	DMP	DMR
RnBeads29,30	R/Bioc	Yes	IDAT, betas, GEO, Bis-Seq bed	Control Plots, PCA/MDS	BMIQ31, SWAN32, dasen33, NOOB34	Yes	limma35,36, t-test, RefFreeEWAS37, rank-based	Aggregate p-value
ChAMP38,39	R/Bioc	No	IDAT, betas	Control Plots, PCA/MDS	BMIQ, FunNorm40, SWAN	Yes	limma	Probe Lasso41, bumphunter42, DMRcate43
SeSAMe44	R/Bioc	No	IDAT	QC statistics	Nonlinear dye44, NOOB	Yes	No	No
Minfi45,46	R/Bioc	No	IDAT, GEO, betas	Control Plots, Beta Density, MDS	SWAN, NOOB, FunNorm, SQN47, Illumina	Yes	limma	bumphunter
shinyÉPICo48	R/Bioc	Yes	IDAT	Beta Density, PCA	As minfi	No	limma	mCSEATest49
ENmix50	R/Bioc	No	IDAT	Control Plots, PCR	Enmix51, RELIC52, RCP53	Yes	No	comb-p54, ipDMR55
MADA56	Web	Yes	IDAT	Beta Density, MDS	As minfi, BMIQ, dasen	No	limma, samr57	Probe Lasso, bumphunter, DMRcate, seqlm58
FOXO BioScience59–61	Python	No	IDAT, GEO, ArrayExpress	Control Plots, Beta Density, MDS	NOOB	No	linear regression, logistic regression	No
DimMer62,63	Java	Yes	IDAT	No	Illumina, SQN	Yes	t-test, linear regression	sliding window

Bioc bioconductor, MDS multidimensional scaling, PCA principal component analysis, PCR principal component regression, DMP differentially methylated position, DMR differentially methylated region.