diggit (version 1.4.0)

print,diggit-method: Basic methods for class diggit

Description

This document lists a series of basic methods for the class diggit

Usage

"print"(x, pval = 0.05)
"show"(object)
"exprs"(object)
"diggitCNV"(x)
"diggitRegulon"(x)
"diggitMindy"(x)
"diggitFcnv"(x)
"diggitMR"(x)
"diggitViper"(x)
"diggitAqtl"(x)
"diggitConditional"(x)
"summary"(object)
"head"(x, rows = 4, cols = 4)
"mindyFiltering"(x, mr = 0.01, mr.adjust = c("none", "fdr", "bonferroni"))

Arguments

x

Object of class diggit

pval

P-value threshold for the conditional analysis

object

Object of class diggit

rows

Integer indicating the maximum number of rows to show

cols

Integer indicating the maximum number of columns to show

mr

Either a numerical value between 0 and 1 indicating the p-value threshold for the Master Regulator (MR) selection, or a vector of character strings listing the MRs

mr.adjust

Character string indicating the multiple hypothesis test correction for the MRs

Value

print returns summary information about the diggit objectshow returns summary information about the object of class diggitexprs returns the ExpressionSet object containing the expression profile datadiggitCNV returns a matrix containing the CNV datadiggitRegulon returns a regulon object containing the transcriptional interactomediggitMindy returns a regulon object containing the post-translational interactomediggitFcnv returns a vector of p-values for the F-CNVsdiggitMR returns a vector of master regulators NESdiggitViper returns a matrix of VIPER resultsdiggitAqtl returns a matrix of aQTLs (p-value)diggitConditional returns a list containing the conditional analysis resultssummary returns the integrated results from the conditional analysishead returns a list containing a reduced view for an object of class diggitmindyFiltering returns a diggit class object with CNV and aQTL slots filtered to contain only MINDy post-translational modulators of the MRs

Examples

data(gbm.expression, package="diggitdata")
data(gbm.cnv, package="diggitdata")
data(gbm.aracne, package="diggitdata")
dobj <- diggitClass(expset=gbmExprs, cnv=gbmCNV, regulon=gbmTFregulon)
print(dobj)
show(dobj)
exprs(dobj)
diggitCNV(dobj)[1:3, 1:3]
diggitRegulon(dobj)
diggitMindy(dobj)
diggitFcnv(dobj)
diggitMR(dobj)
diggitViper(dobj)
diggitAqtl(dobj)
diggitConditional(dobj)
head(dobj)
data(gbm.expression, package="diggitdata")
data(gbm.cnv, package="diggitdata")
data(gbm.mindy, package="diggitdata")
dobj <- diggitClass(expset=gbmExprs, cnv=gbmCNV, mindy=gbmMindy)
dobj <- fCNV(dobj)
dobj
dobj <- mindyFiltering(dobj, mr=c("STAT3", "CEBPD"))
dobj