Table 1.

Parameter settings for the DMR identification methods. Default settings are underlined and in bold font.

Method	Implementation	Input Parameters	Statistics for computing DMR P-value	DMR P-value label in output table
Bumphunter	R/BioC package bumphunter v1.20.0	pickCutoffQ = (0.95, 0.99), maxGap = (200, 250, 500, 750, 1000), nullMethod ="permutation", B=10	permutation distribution based on permuting sample labels	P-value area
Comb-p	Python library comb-p v0.48	--seed (0.001, 0.01, 0.05) --dist (200, 250, 500, 750, 1000)	Stouffer–Liptak statistic	z_p
DMRcate	R/BioC package DMRcate v1.14.0	lambda = (200, 250, 500, 750, 1000), C = (1,2,3,4,5)	Stouffer’s method	Stouffer
Probe Lasso	R/BioC package ChAMP v2.9.10	method = “ProbeLasso”, adjPvalProbe = (0.001, 0.01, 0.05) meanLassoRadius = (375, 700, 1000) minDmrSep = (200, 250, 500, 750, 1000)	Stouffer’s method	dmrP