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UniFilter
to an ExprTreeSet
.
unifilter(xps.expr, filename = character(0), filedir = getwd(), filter = NULL, minfilters = 999, logbase = "log2", group = character(0), treename = "UniTest", xps.fltr = NULL, xps.call = NULL, update = FALSE, verbose = TRUE)
xpsUniFilter(object, ...)
ExprTreeSet
.UniFilter
."0"
, "log"
, "log2"
(default), "log10"
xps.expr
to one of two groups.FilterTreeSet
.CallTreeSet
.TRUE
the existing ROOT filter file filename
will be updated.TRUE
print status information.ExprTreeSet
.unifilter
.AnalysisTreeSet
UniFilter
to the ExprTreeSet
xps.expr
. Slot minfilters
determines the minimum number of initialized filters, which must be satisfied
so that the mask is set to flag=1
. For minfilters=1
at least one filter must be
satisfied, equivalent to logical ‘OR’; for minfilters=999
all filters must be
satisfied, equivalent to logical ‘AND’.
If pre-filtering should be done before applying function unifilter
then a
FilterTreeSet
xps.fltr
must be supplied, created with function
prefilter
.
If method callFilter
was initialized with constructor UniFilter
then CallTreeSet
xps.call
must be supplied, usually created with function
mas5.call
.
UniFilter
, prefilter
## Not run:
# ## first, load ROOT scheme file and ROOT data file
# scheme.test3 <- root.scheme(paste(path.package("xps"),"schemes/SchemeTest3.root",sep="/"))
# data.test3 <- root.data(scheme.test3, paste(path.package("xps"),"rootdata/DataTest3_cel.root",sep="/"))
#
# ## second, create an ExprTreeSet
# data.rma <- rma(data.test3,"tmp_Test3_RMA",tmpdir="",background="pmonly",normalize=TRUE,verbose=FALSE)
# ## note: do not copy/paste this code, it is necessary only because R CMD check fails since it does not find tmp_Test3_RMA.root:
# data.rma@rootfile <- paste(path.package("xps"),"rootdata/tmp_Test3RMA.root",sep="/")
# data.rma@filedir <- paste(path.package("xps"),"rootdata",sep="/")
#
# ## third, construct an UniFilter
# unifltr <- UniFilter(unitest=c("t.test","two.sided","none",0,0.0,FALSE,0.95,TRUE),foldchange=c(1.3,"both"),unifilter=c(0.1,"pval"))
#
# ## finally, create an AnalysisTreeSet
# rma.ufr <- unifilter(data.rma,"tmp_Test3Unifilter",getwd(),unifltr,group=c("GrpA","GrpA","GrpB","GrpB"),verbose=FALSE)
# str(rma.ufr)
# ## End(Not run)
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