Name	Type	Named	Null	Values	Default
analysis.name	character	no	yes		NULL
logging	logical	no	no		TRUE
email	character	no	yes		NULL
assembly	character	no	no		hg19
columns.pairing	integer.vector	yes	yes		NULL
analyze.sites	logical	no	no		TRUE
region.types	character.vector	no	yes		NULL
region.aggregation	character	no	no	(coverage.weighted,min,max,mean,median,sum)	mean
region.subsegments	integer	no	no	[0,	0
region.subsegments.types	character.vector	no	yes		NULL
identifiers.column	character	no	yes		NULL
points.category	integer.vector	no	no		(16,17,3,15,4,7,8)
colors.category	character.vector	no	no		(#1B9E77,#D95F02,#7570B3,#E7298A,#66A61E,#E6AB02,#A6761D,#666666)
colors.gradient	character.vector	no	no		(#132B43,#56B1F7)
min.group.size	integer	no	no	[1,	2
max.group.count	integer	no	yes	[2,	NULL
gz.large.files	logical	no	no		FALSE
strand.specific	logical	no	no		FALSE
replicate.id.column	character	no	yes		NULL
import	logical	no	no		TRUE
import.default.data.type	character	no	no	(data.dir,idat.dir,GS.report,GEO,bed.dir,rnb.set,rnb.set.dir)	idat.dir
import.table.separator	character	no	no		,
import.bed.style	character	no	no	(BisSNP,Encode,EPP,bismarkCytosine,bismarkCov,custom)	BisSNP
import.bed.columns	integer.vector	NULL	no	[1,	(chr=1,start=2,end=3,strand=6,meth=4,coverage=5)
import.bed.frame.shift	integer	no	no		1
import.bed.test	logical	no	no		TRUE
import.bed.test.only	logical	no	no		FALSE
import.skip.object.check	logical	no	no		FALSE
import.idat.chunk.size	integer	no	yes	(1,	NULL
import.gender.prediction	logical	no	no		TRUE
qc	logical	no	no		TRUE
qc.boxplots	logical	no	no		TRUE
qc.barplots	logical	no	no		TRUE
qc.negative.boxplot	logical	no	no		TRUE
qc.snp.heatmap	logical	no	no		TRUE
qc.snp.barplot	logical	no	no		FALSE
qc.snp.boxplot	logical	no	no		FALSE
qc.snp.distances	logical	no	no		TRUE
qc.snp.purity	logical	no	no		FALSE
qc.coverage.plots	logical	no	no		FALSE
qc.coverage.threshold.plot	integer.vector	no	yes	[1,	(1,2,3,4,5,6,7,8,9,10)
qc.coverage.histograms	logical	no	no		TRUE
qc.coverage.violins	logical	no	no		TRUE
qc.sample.batch.size	integer	no	no		500
preprocessing	logical	no	no		TRUE
normalization	logical	no	yes		NULL
normalization.method	character	no	no	(none,bmiq,illumina,swan,minfi.funnorm,wm.dasen,wm.nasen,wm.betaqn,wm.naten,wm.nanet,wm.nanes,wm.danes,wm.danet,wm.danen,wm.daten1,wm.daten2,wm.tost,wm.fuks,wm.swan)	swan
normalization.background.method	character	no	no	(none,methylumi.noob,methylumi.goob,enmix.oob)	methylumi.noob
normalization.plot.shifts	logical	no	no		TRUE
filtering.whitelist	character	no	yes		NULL
filtering.blacklist	character	no	yes		NULL
filtering.context.removal	character.vector	no	yes	(CC,CG,CAG,CAH,CTG,CTH,Other)	(CC,CAG,CAH,CTG,CTH,Other)
filtering.snp	character	no	no	(no,3,5,any,yes)	3
filtering.cross.reactive	logical	no	no		FALSE
filtering.greedycut	logical	no	no		TRUE
filtering.greedycut.pvalue.threshold	double	no	no	[0,1]	0.05
filtering.greedycut.rc.ties	character	no	no	(any,column,row)	row
filtering.sex.chromosomes.removal	logical	no	no		FALSE
filtering.missing.value.quantile	double	no	no	[0,1]	1
filtering.coverage.threshold	integer	no	no	[0,	5
filtering.low.coverage.masking	logical	no	no		FALSE
filtering.high.coverage.outliers	logical	no	no		FALSE
filtering.deviation.threshold	double	no	no	[0,1]	0
inference	logical	no	no		FALSE
inference.targets.sva	character.vector	no	no		()
inference.reference.methylome.column	character	no	yes		NULL
inference.max.cell.type.markers	integer	no	yes	[1,	50000
inference.top.cell.type.markers	integer	no	no	[1,	500
inference.sva.num.method	character	no	no	(be,leek)	leek
inference.age.column	character	no	no		age
inference.age.prediction	logical	no	no		TRUE
inference.age.prediction.training	logical	no	no		FALSE
inference.age.prediction.predictor	character	no	yes		NULL
inference.age.prediction.cv	logical	no	no		FALSE
exploratory	logical	no	no		TRUE
exploratory.columns	integer.vector	no	yes		NULL
exploratory.top.dimensions	integer	no	no	[0,	0
exploratory.principal.components	integer	no	no	[0,10]	8
exploratory.correlation.pvalue.threshold	double	no	no	[0,1]	0.01
exploratory.correlation.permutations	integer	no	no	[0,	10000
exploratory.correlation.qc	logical	no	no		TRUE
exploratory.beta.distribution	logical	no	no		TRUE
exploratory.intersample	logical	no	no		TRUE
exploratory.deviation.plots	logical	no	yes		NULL
exploratory.clustering	character	no	no	(all,none,top)	all
exploratory.clustering.top.sites	integer.vector	no	no	[1,	(1000)
exploratory.clustering.heatmaps.pdf	logical	no	no		FALSE
exploratory.region.profiles	character.vector	no	yes		(genes,promoters,cpgislands)
exploratory.gene.symbols	character.vector	no	yes		NULL
exploratory.custom.loci.bed	character	no	yes		NULL
differential	logical	no	no		TRUE
differential.site.test.method	character	no	no	(limma,ttest,refFreeEWAS)	limma
differential.permutations	integer	no	no	[0,	0
differential.comparison.columns	integer.vector	no	yes		NULL
differential.comparison.columns.all.pairwise	integer.vector	no	yes		NULL
covariate.adjustment.columns	integer.vector	no	yes		NULL
differential.adjustment.sva	logical	no	no		TRUE
differential.adjustment.celltype	logical	no	no		TRUE
differential.enrichment	logical	no	no		FALSE
differential.report.sites	logical	no	no		TRUE
export.to.bed	logical	no	no		TRUE
export.to.trackhub	character.vector	no	yes	(bigBed,bigWig)	(bigBed,bigWig)
export.to.csv	logical	no	no		FALSE
export.to.ewasher	logical	no	no		FALSE
export.types	character.vector	no	yes		(sites)
colors.meth	character.vector	no	no		(#AD0021,#909090,#39278C)
colors.3.gradient	character.vector	no	no		(#832424,#FFFFFF,#3A3A98)
logging.memory	logical	no	no		TRUE
logging.disk	logical	no	no		FALSE
logging.exit.on.error	logical	no	no		FALSE
distribution.subsample	integer	no	no	[0,	1000000
disk.dump.big.matrices	logical	no	no		TRUE
disk.dump.bigff	logical	no	no		FALSE
disk.dump.bigff.finalizer	character	no	no	(delete,close)	delete
enforce.memory.management	logical	no	no		FALSE
enforce.destroy.disk.dumps	logical	no	no		FALSE
