RTN (version 1.10.0)

tna.get: Get information from individual slots in a TNA object.

Description

Get information from individual slots in a TNA object. Available results from a previous analysis can be selected either by pvalue cutoff (default) or top significance.

Usage

tna.get(object, what="summary", order=TRUE, ntop=NULL, reportNames=TRUE, 
idkey=NULL)

Arguments

object

an object of class 'TNA' TNA-class.

what

a single character value specifying which information should be retrieved from the slots. Options: 'tnet', 'refnet', 'tfs', 'pheno', 'regulons','refregulons', 'para', 'mra', 'gsea1', 'gsea2','overlap', 'synergy', 'shadow', 'summary' and 'status'. Regulons can also be retrieved mapped to the available phenotype vector ('regulons.and.pheno' or 'refregulons.and.pheno') or mapped to the assiged mode of action ('regulons.and.mode' or 'refregulons.and.mode').

order

a single logical value specifying whether or not the output data should be ordered by significance. Valid only for 'gsea1', 'gsea2', 'overlap', 'synergy' or 'shadow' options.

ntop

a single integer value specifying to select how many results of top significance from 'gsea', 'overlap', 'synergy' or 'shadow' options.

reportNames

a single logical value specifying to report regulons with 'names' (when reportNames=TRUE) or not (when reportNames=FALSE). This option is effective only if transcription factors were named with alternative identifiers in the pre-processing analysis. It takes effect on 'mra', 'gsea', 'overlap', 'synergy' and 'shadow' options.

idkey

an optional single character value specifying an ID name from the available 'TNA' annotation to be used as alias for data query outputs (obs. it has no effect on consolidated tables).

Value

get the slot content from an object of class 'TNA' TNA-class.

Examples

data(dt4rtn)
tfs4test<-c("PTTG1","E2F2","FOXM1","E2F3","RUNX2")
rtni <- new("TNI", gexp=dt4rtn$gexp, transcriptionFactors=dt4rtn$tfs[tfs4test])

## Not run: 
# 
# rtni <- tni.preprocess(rtni,gexpIDs=dt4rtn$gexpIDs)
# rtni<-tni.permutation(rtni)
# rtni<-tni.bootstrap(rtni)
# rtni<-tni.dpi.filter(rtni)
# rtna<-tni2tna.preprocess(rtni, phenotype=dt4rtn$pheno, hits=dt4rtn$hits, phenoIDs=dt4rtn$phenoIDs)
# 
# # run MRA analysis pipeline
# rtna <- tna.mra(rtna)
# 
# # check summary
# tna.get(rtna,what="summary")
# 
# # get results, e.g., MRA analysis
# tna.get(rtna,what="mra")
# ## End(Not run)