name	desc	default
analysis.name	One-elementcharactervector storing a short title of the analysis. If specified, this name appears at the page title of every report.	NULL
logging	Flag indicating if logging functionality is enabled in the automatic runs of the pipeline.	TRUE
email	Email address associated with the analyses.	NULL
assembly	Genome assembly to be used. Currently only important for bisulfite mode. The supported genomes returned by the functionrnb.get.assemblies.	"hg19"
analyze.sites	Flag indicating if analysis on site or probe level is to be conducted. Note that the preprocessing module always operates on the site level (only), regardless of the value of this option.	TRUE
region.types	Region types to carry out analysis on, in the form of acharactervector.NULL(default value) signifies that all available region annotations (as returned byrnb.region.types) are summarized upon loading and normalization, and the other modules analyze all regions summarized in the dataset. If this option is set to an empty vector, analysis on the region level is skipped.	NULL
region.aggregation	Aggregation function to apply when calculating the methylation value for a region based on the values of the CpGs associated with that region. Accepted values for this function are"min","max","mean"(default),"median","sum","coverage.weighted". The last method is applicable only for sequencing-based methylation datasets. It computes the weighted average of the values of the associated CpGs, whereby weights are calculated based on the coverages of the respective sites.	"mean"
region.subsegments	If a number larger than 1 is specified,RnBeadswill subdivide each region specified in theregion.typesoption into subsegments containing on averageregion.subsegmentssites per subsegment. This is done by clustering the sites within each regions according to their genomic coordinates. These subsegments are then used for subsequent analysis. Use cautiously as this will significantly increase the runtime of the pipeline.	0
region.subsegments.types	The region types to which subsegmentation will be applied. Defaults toregion.typeswhen set toNULL.	NULL
identifiers.column	Column name or index in the table of phenotypic information to be used when plotting sample identifiers. If this option isNULL, it points to a non-existing column or a column that does not list IDs, the default identifiers are used. These are the row names of the sample phenotype table (and the column names of the beta value matrix).	NULL
colors.category	charactervector of length 2 or more giving the color scheme for displaying categorical trait values in plots. RnBeads denotes missing values (NA) by grey, therefore, it is not recommended to include shades of grey in this vector. The default value of this option is the result of the"Dark2"palette ofRColorBrewerwith 8 values.	c("#1B9E77","#D95F02",...)
colors.gradient	charactervector of length 2 or more giving the color scheme for displaying continuous (gradient) trait values in plots.RnBeadsinterpolates between the color values.	c("#132B43","#56B1F7")
min.group.size	Minimum number of samples each subgroup defined by a trait, in order for this trait to be considered in the methylation profiles and in the differential methylation modules. This must be a positiveinteger.	2
max.group.count	Maximum number of subgroups defined by a trait, in order for this trait to be considered in the methylation profiles and in the differential methylation modules. This must be anintegerof value2or more. As a special case, a value ofNULL(default) indicates that the maximum number of subgroups is the number of samples in an analysis minus1, i.e. traits with all unique values will be ignored.	NULL
replicate.id.column	Column name in the sample annotation table that indicates sample replicates. Replicates are expected to contain the same value. Samples without replicates should contain unique or missing values. If this option isNULL(default), replicate handling is disabled.	NULL
gz.large.files	Flag indicating whether large output files should be compressed (in.gzformat).	FALSE
import	Flag controlling whether data import report should be generated. This option be set toFALSEonly when the provided data source is an object of type RnBSet, i.e. the data has been previously loaded byRnBeads.	TRUE
import.default.data.type	Type of data assumed to be supplied by default (Infinium 450k microarray). For sequencing data set this tobs.bed.dirand save the options. Seernb.execute.importfor further details.	"infinium.idat.dir"
import.table.separator	Separator used in the plain text data tables. Seernb.execute.importfor details.	","
import.bed.style	Preset for bed-like formats."BisSNP", "Encode","EPP", "bismarkCytosine", "bismarkCov"are currently supported. See theRnBeadsvignette and the FAQ section on the website for more details.	"BisSNP"
import.bed.columns	Column indices in the supplied BED file with DNA methylation information. These are represented by a namedintegervector, in which the names are:"chr","start","end","strand","meth","coverage","c"and"t". These names correspond the columns for chromosome, start position, end position, strand, methylation degree, read coverage, number of reads with C and number of reads with T, respectively. Methylation degree and/or read coverage, if not specified, are inferred from the values in the columns"c"and"t". Further details and examples of BED files can be found in Section 4.1 of the RnBeads vignette.	NA
import.bed.frame.shift	Singleton of typeintegerspecifying the frame shift between the coordinates in the input BED file and the corresponding genomic reference. This (integer) value is added to the coordinates from the BED file before matching the methylation sites to the annotated ones.	1
import.bed.test	Perform a small loading test, by reading 1000 rows from each BED file, after which normal loading is performed. SeeRnBeadsvignette and the FAQ section on the website for more details.	TRUE
import.bed.test.only	Perform only the small loading test, and skip loading all the data.	FALSE
import.skip.object.check	Skip the check of the loaded RnBSet object after loading. Helps with keeping the memory profile down	FALSE
import.gender.prediction	Flag indicating if gender prediction is to be performed. Gender prediction is supported for Infinium 450k, EPIC and bisulfite sequencing datasets with signal intensity or coverage information. The value of this option is ignored for 27k datasets.	TRUE
qc	Flag indicating if the quality control module is to be executed.	TRUE
qc.boxplots	[Microarrays] Add boxplots for all types of quality control probes to the quality control report. The boxplots give signal distribution across samples.	TRUE
qc.barplots	[Microarrays] Add barplots for each quality control probes to the quality control report.	TRUE
qc.negative.boxplot	[Microarrays] Add boxplot of negative control probe intensities for all samples.	TRUE
qc.snp.heatmap	[Microarrays] Flag indicating if a heatmap of the beta values for all SNP probes is to be geneerated.	TRUE
qc.snp.barplot	[Microarrays] Add bar plots of the beta-values observed for each SNP-calling probe.	FALSE
qc.snp.boxplot	[Microarrays] Add boxplot of beta-values for the SNP-calling probes.	FALSE
qc.snp.distances	[Microarrays] Flag indicating if intersample distances based on the beta values of SNP probes are to be displayed. This can help identify genetically similar or identical samples.	TRUE
qc.snp.purity	[Microarrays] Flag indicating if genetic purity should be estimated based on the beta values of SNP probes.	FALSE
qc.sample.batch.size	[Microarrays] Maximal number of samples included in a single quality control barplot and negative control boxplot.	50
qc.coverage.plots	[Bisulfite sequencing] Add genome-wide sequencing coverage plot for each sample.	FALSE
qc.coverage.threshold.plot	[Bisulfite sequencing] Values for coverage cutoffs to be shown in a coverage thresholds plot. This must be anintegervector of positive values. Setting this to an empty vector disables the coverage thresholds plot.	1:10
qc.coverage.histograms	[Bisulfite sequencing] Add sequencing coverage histogram for each sample.	FALSE
qc.coverage.violins	[Bisulfite sequencing] Add sequencing coverage violin plot for each sample.	FALSE
preprocessing	Flag controlling whether the data should be preprocessed (whether quality filtering and in case of Infinium microarray data normalization should be applied).	TRUE
normalization	Flag controlling whether the data should be normalized and normalization report generated. Setting this toNULL(default) enables this step for analysis on Infinium datasets, but disables it in case of sequencing-based datasets. Note that normalization is never applied in sequencing datasets; if this flag is enabled, it will lead to a warning message.	NULL
normalization.method	Normalization method to be applied, or"none". Multiple normalization methods are supported:"illumina"-methylumi-implemented Illumina scaling normalization;"swan"(default) - SWAN-normalization by Gordon et al., as implemented inminfi;"bmiq"- beta-mixture quantile normalization method by Teschendorff et al; as well as"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"and"wm.swan"- all normalization methods implemented in thewateRmelonpackage. When setting this option to a specific algorithm, make sure its dedicated package is installed.	"swan"
normalization.background.method	A character singleton specifying which background subtraction is to be performed during normalization. The following values are accepted:"none","methylumi.noob","methylumi.goob","methylumi.lumi"and"enmix.oob".	"methylumi.noob"
normalization.plot.shifts	Flag indicating if the report on normalization should include plots of shifts (degrees of beta value correction).	TRUE
filtering.whitelist	Name of a file specifying site or probe identifiers to be whitelisted. Every line in this file must contain exactly one identifier. The whitelisted sites are always retained in the analysed datasets, even if filtering criteria or blacklisting requires their removal. For Infinium studies, the file must contain Infinium probe identifiers. For bisulfite sequencing studies, the file must contain CpG positions in the form "chromosome:coordinate" (1-based coordinate of the cytosine), e.g.chr2:48607772. Unknown identifiers are silently ignored.	NULL
filtering.blacklist	Name of a file specifying site or probe identifiers to be blacklisted. Every line in this file must contain exactly one identifier. The blacklisted sites are removed from the analysed datasets as a first step in the preprocessing module. For Infinium studies, the file must contain Infinium probe identifiers. For bisulfite sequencing studies, the file must contain CpG positions in the form "chromosome:coordinate" (1-based coordinate of the cytosine), e.g.chr2:48607772. Unknown identifiers are silently ignored.	NULL
filtering.context.removal	charactervector giving the list of probe context types to be removed as a filtering step. Possible context values are"CC","CG","CAG","CAH","CTG","CTH"and"Other". Probes in the second context measure CpG methylation; the last context denotes probes dedicated to SNP detection. Setting this option toNULLor an empty vector effectively disables the step of context-specific probe removal.	c("CC","CAG",...)
filtering.snp	Removal of sites or probes based on overlap with SNPs. The accepted values for this option are:"no"no SNP-based filtering;"3"filter out a probe when the last 3 bases in its target sequence overlap with SNP;"5"filter out a probe when the last 5 bases in its target sequence overlap with SNP;"any"or"yes"filter out a CpG site or probe when any base in its target sequence overlaps with SNP.Bisulfite sequencing datasets operate on sites instead of probes, therefore, the values"3"and"5"are treated as"yes".	"3"
filtering.cross.reactive	Flag indicating if the removal of potentially cross-reactive probes should be performed as a filtering step in the preprocessing module. A probes whose sequence maps to multiple genomic locations (allowing up to 3 mismatches) is cross-reactive.	FALSE
filtering.greedycut	Flag indicating if the Greedycut procedure should be run as a filtering step in the preprocessing module.NULL(default) indicates that Greedycut will be run for array-based datasets, but not for sequencing-based datasets.	NULL
filtering.greedycut.pvalue.threshold	Threshold for the detection p-value to be used in Greedycut. This is a value between 0 and 1. This option has effect only whenfiltering.greedycutisTRUE.	0.05
filtering.greedycut.rc.ties	Indicator of what the behaviour of Greedycut should be in case of ties between the scores of rows (probes) and columns (samples). The value of this option must be one of"row","column"or"any"; the last one indicating random choice. This option has effect only whenfiltering.greedycutisTRUE.	"row"
filtering.sex.chromosomes.removal	Flag indicating if the removal of probes located on sex chromosomes should be performed as a filtering step.	FALSE
filtering.missing.value.quantile	Number between 0 and 1, indicating the fraction of allowed missing values per site. A site is filtered out when its methylation beta values areNAs in a larger fraction of samples than this threshold. Setting this option to 1 (default) retains all sites, and thus effectively disables the missing value filtering step in the preprocessing module. If this is set to 0, all sites that contain missing values are filtered out.	1
filtering.coverage.threshold	Threshold for minimal acceptable coverage. This must be a non-negative value. Setting this option to 0 (zero) effectively considers any known or unknown read coverage for sufficiently deep.	5
filtering.low.coverage.masking	Flag indicating whether methylation values for low coverage sites should be set to missing. In combination withfiltering.missing.value.quantilethis can lead to the removal of sites.	FALSE
filtering.high.coverage.outliers	(Bisulfite sequencing mode) Flag indicating whether methylation sites with a coverage of more than 10 times the 95-percentile of coverage should be removed.	FALSE
filtering.deviation.threshold	Threshold used to filter probes based on the variability of their assigned beta values. This must be a real value between 0 and 1, denoting minimum standard deviation of the beta values in one site across all samples. Any sites that have standard deviation lower than this threshold are filtered out. Note that sites with undetermined varibility, that is, sites for which there are no measurements (all beta values areNAs), are retained. Setting this option to 0 (default) disables filtering based on methylation variability.	0
imputation.method	Character indicating which imputation method should be used to replace missing values. This option has to be one of the following values"none","mean.cpgs","mean.samples","random"or"knn". Setting this option to"none"inactivates imputation (default).	"none"
inference	Flag indicating if the covariate inference analysis module is to be executed.	FALSE
inference.targets.sva	Column names in the sample annotation table for which surrogate variable analysis (SVA) should be conducted. An empty vector (default) means that SVA is skipped.	character()
inference.reference.methylome.column	Column name in the sample annotation table giving the assignment of samples to reference methylomes. The target samples should haveNAvalues in this column.	character()
inference.max.cell.type.markers	Number of most variable CpGs which are tested for association with the reference cell types. Setting this option toNULLforces the algorithm to use all available sites in the dataset, and may greatly increase the running time for cell type comoposition estimation.	50000
inference.top.cell.type.markers	Number of top cell type markers used for determining cell type contributions to the target DNA methylation profiles using the projection method of Houseman et al.	500
inference.sva.num.method	Name of the method to be used for estimating the number of surrogate variables. must be either 'leek' or 'be', Seesvafunction for details.	"leek"
inference.age.column	Name of the column in which the ages of the donors are annotated. This function can be of numeric, string or  factor format.	"age"
inference.age.prediction	Flag indicating if the epigenetic age prediction within the inference module is to be executed.	TRUE
inference.age.prediction.training	Flag indicating if a new predictor should be created based on the provided data set.	FALSE
inference.age.prediction.cv	Flag indicating if predictive power of a predictor that was trained in that run of the age prediction should be assessed by cross-validation. This option only has an influence ifinference.age.prediction.training= TRUE	FALSE
exploratory	Flag indicating if the exploratory analysis module is to be executed.	TRUE
exploratory.columns	Traits, given as column names or indices in the sample annotation table, to be used in the exploratory analysis. These traits are used in multiple steps in the module: they are visualized using point types and colors in the dimension reduction plots; tested for strong correlations and associations with principal components in a methylation space; used to define groups when plotting beta distributions and/or inter-sample methylation variability. The default value of this parameter -NULL- indicates that columns should be automatically selected; seernb.sample.groupsfor how this is done.	NULL
exploratory.top.dimensions	Number of most variable probes, sites or regions to select prior to performing dimension reduction techniques and tests for associations. Preselection can significantly reduce the running time and memory usage in the exploratory analysis module. Setting this number to zero (default) disables preselection.	0
exploratory.principal.components	Maximum number of principal components to be tested for associations with other factors, such as control probe states and sample traits. This must be anintegervalue between0and10. Setting this option to0disables such tests.	8
exploratory.correlation.pvalue.threshold	Significance threshold for a p-value resulting from applying a test for association. This is a value between 0 and 1.	0.01
exploratory.correlation.permutations	Number of permutations in tests performed to check for associations between traits, and between control probe intensities and coordinates in the prinicipal component space. This must be a non-negativeinteger. Setting this option to0disables permutation tests.	10000
exploratory.correlation.qc	[Infinium 450k] Flag indicating if quality-associated batch effects should be studied. This amounts to testing for associations between intensities of quality control probes and principal components. This option has effect only whenexploratory.principal.componentsis non-zero.	TRUE
exploratory.beta.distribution	Flag indicating whether beta value distributions for sample groups and probe or site categories should be computed.	TRUE
exploratory.intersample	Flag indicating if methylation variability in sample groups should be computed as part of the exploratory analysis module.	TRUE
exploratory.deviation.plots	Flag indicating if the inter-sample methylation variability step in the exploratory analysis module should include deviation plots. Deviation plots show intra-group methylation variability at the covered sites and regions. Setting this option toNULL(default) enables deviation plots on Infinium datasets, but disables them in case of sequencing-based datasets, because their generation can be very computationally intensive. This option has effect only whenexploratory.intersampleisTRUE.	NULL
exploratory.clustering	Which sites should be used by clustering algorithms in the exploraroty analysis module.RnBeadsperforms several algorithms that cluster the samples in the dataset. If this option is set to"all"(default), clustering is performed using all sites; a value of"top"indicates that only the most variable sites are used (see the optionexploratory.clustering.top.sites); and"none"disables clustering.	"all"
exploratory.clustering.top.sites	Number of most variable sites to use when visualizing heatmaps. This must be a non-emptyintegervector containing positive values. This option is ignored whenexploratory.clusteringis"none".	1000
exploratory.clustering.heatmaps.pdf	Flag indicating if the generated methylation value heatmaps in the clustering section of the exploratory analysis module should be saved as PDF files. Enabling this option is not recommended for large values ofexploratory.clustering.top.sites(more than 200), because heatmaps might generate very large PDF files.	FALSE
exploratory.region.profiles	Region types for generating regional methylation profiles. IfNULL(default), regional methylation profiles are created only for the region types that are available for the targeted assembly and summarized in the dataset of interest. Setting this option to an empty vector disables the region profiles step in the exploratory analysis module.	NULL
exploratory.gene.symbols	A list of gene symbols to be used for custom locus profiling. Locus views will be generated for these genes.	NULL
exploratory.custom.loci.bed	Path to a bed file containing custom genomic regions. Locus views will be generated for these regions.	NULL
differential	Flag indicating if the differential methylation module is to be executed.	TRUE
differential.site.test.method	Method to be used for calculating p-values on the site level. Currently supported options are "ttest" for a (paired) t-test and "limma" for a linear modeling approach implemented in thelimmapackage for differential expression in microarrays.	"limma"
differential.variability	Flag indicating if differential variability analysis is to be conducted. If TRUE, the method specified indifferential.variability.methodis applied to detect sites that show differential variability between the groups that are specified.	FALSE
differential.variability.method	Method to be used for calculating p-values on the differential variable sites. Currently supported options are "diffVar" implemented in themissMethylpackage and "iEVORA".	"diffVar"
differential.permutations	Number of permutation tests performed to compute the p-value of rank permutation tests in the differential methylation analysis. This must be a non-negativeinteger. Setting this option to0(default) disables permutation tests for rank permutations. Note that p-values for differential methylation are computed and also considered for the ranking in any case.	0
differential.comparison.columns	Column names or indices in the table of the sample annotation table to be used for group definition in the differential methylation analysis. The default value -NULL- indicates that columns should be automatically selected. Seernb.sample.groupsfor how this is done. By default, the comparisons are done in a one vs. all manner if there are multiple groups defined in a column.	NULL
differential.comparison.columns.all.pairwise	Column names or indices in the table of sample annotation table to be used for group definition in the differential methylation analysis in which all pairwise comparisons between groups should be conducted (the default is one vs all if multiple groups are specified in a column). Caution: for large numbers of sample groups this can lead to combinatorial explosion and thus to huge runtimes. A value ofNULL(default) indicates that no column is selected for all pairwise comparisons explicitely. If specified, the selected columns must be a subset of the columns that will be selected according to thedifferential.comparison.columnsoption.	NULL
covariate.adjustment.columns	Column names or indices in the table of phenotypic information to be used for confounder adjustment in the differential methylation analysis. Currently this is only supported fordifferential.site.test.method=="limma".	NULL
columns.pairing	A NAMED vector containing for each column name for which paired analysis should be performed (say columnA) the name or index of another column (say columnB) in which same values indicate the same pairing. columnA should be the name of the value columnB in this vector. For more details seernb.sample.groups	NULL
differential.adjustment.sva	Flag indicating if the differential methylation analysis should account for Surrogate Variables. IfTRUE,RnBeadslooks for overlaps between thedifferential.comparison.columnsandinference.targets.svaoptions and include the surrogate variables as confounding factors only for these columns. In other words, it will only have an effect if the corresponding inference option (seeinference.targets.svaoption for details) is enabled. Currently this is only supported fordifferential.site.test.method=="limma".	TRUE
differential.adjustment.celltype	Should the differential methylation analysis account for celltype using the reference based Houseman method. It will only have an effect if the corresponding inference option is enabled (seeinference.reference.methylome.columnoption for details). Currently this is only supported fordifferential.site.test.method=="limma".	TRUE
differential.enrichment.go	Flag indicating whetherGene Ontology(GO)-enrichment analysis is to be conducted on the identified differentially methylated regions.	FALSE
differential.enrichment.lola	Flag indicating whetherLOLA-enrichment analysis is to be conducted on the identified differentially methylated regions.	FALSE
differential.enrichment.lola.dbs	Vector of directories containing LOLA databases. The following placeholders are allowed which will automatically download corresponding databases from the internet:"${LOLACore}"and"${LOLAExt}"for the Core and Extended LOLA Databases respectively.	c("${LOLACore}")
differential.report.sites	Flag indicating whether a section corresponding to differential site methylation should be added to the report. Has no effect on the actual analysis, just the report. To disable differential site methylation analysis entirely use theanalyze.sitesoption.	TRUE
export.to.bed	Flag indicating whether the data should be exported to bed files.	TRUE
export.to.trackhub	charactervector specifying which data types should be exported toTrack hub directories. Possible values in the vector are"bigBed"and"bigWig". When this options is set toNULL, track hub export is disabled. Note that if"bigBed"is contained in this option, bed files are created automatically.	c("bigBed","bigWig")
export.to.csv	Flag indicating whether methylation value matrices are to be exported to comma-separated value (CSV) files.	FALSE
export.to.ewasher	Flag indicating whether methylation values and differential methylation analysis settings should be exported to a format compatible with FaST-LMM-EWASher, a tool for adjusting for cell-type compositions. SeeZou, J., et al., Nature Methods, 2014for further details on the tool.	FALSE
export.types	charactervector of sites and region names to be exported. IfNULL, no region methylation values are exported.	"sites"
disk.dump.big.matrices	Flag indicating whether big tables should be stored on disk rather than in main memory in order to keep memory requirements down. May slow down analysis!	TRUE
logging.exit.on.error	Flag indicating if the active R session should be terminated when an error is encountered during execution.	FALSE
distribution.subsample	When plotting methylation value distributions, this threshold specifies the number of observations drawn per group. Distributions are estimated and plotted based on these random subsamples. This approach can significantly reduce the memory requirements of the preprocessing and exploratory analysis modules, where methylation value distributions are plotted. Setting this to0disables subsampling. More information is presented the Details section ofrnb.step.betadistribution	1000000
enforce.memory.management	Flag indicating whether in some places of the code memory management should actively being enforced in order to achieve a better memory profile. I.e. garbage collection, variable removal is conducted actively. May slow down analysis.	FALSE
enforce.destroy.disk.dumps	Flag indicating whether disked dumped big matrices (seedisk.dump.big.matricesoption) should actively be deleted when RnBSets are modified. You should switch it toTRUEwhendisk.dump.big.matricesisTRUEand the amount of hard drive space is also limited.	FALSE
differential.residuals.output	character controls whether limma residual matrices are retained and/or exported. Allowed values: `NULL` (default), `csv`, `object`. If `object` selected, residual matrices are stored in the diffMeth object. `csv` would also export residuals as csv files.	NULL
differential.report.heatmaps	Flag indicating whether a section corresponding to differential methylation heatmaps should be added to the report.	TRUE
differential.heatmap.top.features	Integer number of top-ranked loci to display in each differential methylation heatmap	100
differential.heatmap.cluster.rows	 Flag indicating whether rows (loci) should be clustered in differential methylation heatmaps.	TRUE
differential.heatmap.cluster.columns	Flag indicating whether columns (samples) should be clustered in differential methylation heatmaps.	TRUE
differential.heatmap.show.row.names	Flag indicating whether row names should be shown in differential methylation heatmaps.	FALSE
differential.heatmap.show.column.names	Flag indicating whether sample names should be shown in differential methylation heatmaps.	FALSE