tna.synergy {RTN} | R Documentation |
This function takes a TNA object and returns the results of the synergy analysis over a list of regulons in a transcriptional network (with multiple hypothesis testing corrections).
tna.synergy(object, pValueCutoff=0.05, pAdjustMethod="BH", minRegulonSize=15, minIntersectSize=1, nPermutations=1000, exponent=1, tnet="ref", orderAbsValue=TRUE, stepFilter=TRUE, tfs=NULL, verbose=TRUE)
object |
a preprocessed object of class 'TNA' |
pValueCutoff |
a single numeric value specifying the cutoff for p-values considered significant. |
pAdjustMethod |
a single character value specifying the p-value adjustment method to be used (see 'p.adjust' for details). |
minRegulonSize |
a single integer or numeric value specifying the minimum number of elements in a regulon that must map to elements of the gene universe. Gene sets with fewer than this number are removed from the analysis. |
minIntersectSize |
a single integer or numeric value specifying the minimum number of elements in the intersect between any two regulons in the synergy analysis (as percentage value). |
nPermutations |
a single integer or numeric value specifying the number of permutations for deriving p-values in GSEA. |
exponent |
a single integer or numeric value used in weighting phenotypes in GSEA (see 'gseaScores' function at HTSanalyzeR). |
tnet |
a single character value specifying which transcriptional network should to used to compute the synergy and shadow analyses. Options: "dpi" and "ref". |
orderAbsValue |
a single logical value indicating whether the values should be converted to absolute values and then ordered (if TRUE), or ordered as they are (if FALSE). |
stepFilter |
a single logical value specifying to use a step-filter algorithm removing
non-significant regulons derived from |
tfs |
an optional vector with transcription factor identifiers (this option overrides the 'stepFilter' argument). |
verbose |
a single logical value specifying to display detailed messages (when verbose=TRUE) or not (when verbose=FALSE). |
a data frame in the slot "results", see 'synergy' in tna.get
.
Mauro Castro
data(tniData) data(tnaData) ## Not run: 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) rtna <- tni2tna.preprocess(rtni, phenotype=tnaData$phenotype, hits=tnaData$hits, phenoIDs=tnaData$phenoIDs) #run synergy analysis pipeline rtna <- tna.synergy(rtna, stepFilter=FALSE) #get results tna.get(rtna, what="synergy") # run parallel version with SNOW package! library(snow) options(cluster=makeCluster(4, "SOCK")) rtna <- tna.synergy(rtna,stepFilter=FALSE) stopCluster(getOption("cluster")) ## End(Not run)