tni.overlap.genesets {RTN} | R Documentation |
This function tests the overlap between gene sets and regulons.
tni.overlap.genesets(object, geneSetList, regulatoryElements = NULL, minGeneSetSize = 15, sizeFilterMethod="posORneg", method = c("HT","JC"), pValueCutoff = 0.05, pAdjustMethod = "BH", verbose = TRUE)
object |
a preprocessed object of class 'TNI' |
geneSetList |
a list with gene sets. |
regulatoryElements |
a vector of valid regulatory elements (e.g. transcription factors). |
minGeneSetSize |
a single integer or numeric value specifying the minimum number of elements in a gene set that must map to elements of the gene universe. Gene sets with fewer than this number are removed from the analysis. |
sizeFilterMethod |
a single character value specifying the use of the 'minGeneSetSize' argument, which is applyed to regulon's positive and negative targets. Options: "posANDneg", "posORneg", "posPLUSneg". For "posANDneg", the number of both positive and negative targets should be > 'minGeneSetSize'; for "posORneg", the number of either positive or negative targets should be > 'minRegulonSize'; and for "posPLUSneg", the number of all targets should be > 'minGeneSetSize'. |
method |
a string specifying the method used to assess the association between gene sets and regulons (see 'Details'). |
pValueCutoff |
a single numeric value specifying the cutoff for p-values considered significant (this parameter only affects the 'HT' option). |
pAdjustMethod |
a single character value specifying the p-value adjustment method to be used (see 'p.adjust' for details) (this parameter only affects the 'HT' option). |
verbose |
a single logical value specifying to display detailed messages (when verbose=TRUE) or not (when verbose=FALSE). |
The 'HT' option assesses the overlap between gene sets and regulons using a hypergeometric test, and returns a data frame with the overlap statistics. The 'JC' option assesses the overlap between gene sets and regulons using the Jaccard Coefficient (JC), and retuns a matrix with JC values.
Either a data frame or a numeric matrix with association statistics between gene sets vs. regulons.
Mauro Castro
data(tniData) ## Not run: #compute regulons rtni <- tni.constructor(expData=tniData$expData, regulatoryElements=c("PTTG1","E2F2","FOXM1","E2F3","RUNX2"), rowAnnotation=tniData$rowAnnotation) rtni <- tni.permutation(rtni) rtni <- tni.bootstrap(rtni) rtni <- tni.dpi.filter(rtni) #load a gene set collection #here, we build three random gene sets for demonstration geneset1 <- sample(tniData$rowAnnotation$SYMBOL,50) geneset2 <- sample(tniData$rowAnnotation$SYMBOL,50) geneset3 <- sample(tniData$rowAnnotation$SYMBOL,50) geneSetList <- list(geneset1=geneset1, geneset2=geneset2, geneset3=geneset3) #run the overlap analysis ovstats <- tni.overlap.genesets(rtni, geneSetList, pValueCutoff = 1) ## End(Not run)