get.comparison.info(x, pheno.cols = rnb.getOption("differential.comparison.columns"), region.types = rnb.region.types.for.analysis(x), pheno.cols.all.pairwise = rnb.getOption("differential.comparison.columns.all.pairwise"), columns.pairs = rnb.getOption("columns.pairing"), columns.adj = rnb.getOption("covariate.adjustment.columns"), adjust.sva = rnb.getOption("differential.adjustment.sva"), pheno.cols.adjust.sva = rnb.getOption("inference.targets.sva"), adjust.celltype = rnb.getOption("differential.adjustment.celltype"), adjust.na.rm = TRUE)
RnBSet
objectx
on which the dataset should be partitioned. Those columns are required to be factors or logical.
In case of factors, each group in turn will be compared to all other groupspheno(x)
on which all pairwise comparisons should be conducted.
A value of NULL
indicates no columns.rnb.sample.groups
. See its documentation for details.adjust.sva==TRUE
. Only the intersection of
pheno.cols
and pheno.cols.adjust.sva
is considered for SVA adjustment.rnb.execute.ct.estimation
for details.comparison
pheno.colname
group.names
group.inds
paired
adj.sva
adj.celltype
adjustment.table
NULL
if the comparison is not adjustedregion.types
library(RnBeads.hg19)
data(small.example.object)
logger.start(fname=NA)
cmp.info <- get.comparison.info(rnb.set.example,pheno.cols=c("Sample_Group","Treatment"))
cmp.info[[1]]
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