tni.annotate.samples {RTN} | R Documentation |
This function calculates an enrichment score between gene sets and samples.
tni.annotate.samples(object, geneSetList, minGeneSetSize = 15, exponent = 1, verbose = TRUE)
object |
a preprocessed object of class 'TNI' |
geneSetList |
a list with gene sets. |
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. |
exponent |
a single integer or numeric value used in weighting phenotypes in GSEA (this parameter only affects the GSEA statistics). |
verbose |
a single logical value specifying to display detailed messages (when verbose=TRUE) or not (when verbose=FALSE). |
Using the samples available in the provided TNI object, the 'tni.annotate.samples' calculates the enrichment of each sample for each gene set. First, a gene-wise differential expression (DEG) signature is generated by comparing the expression of a given sample with the avarage expression of all samples. The DEG signature is regarded as a the sample phenotype, representing the relative expression of the sample's genes in the cohort. Then a single-sample Gene Set Enrichment Analysis (ssGSEA) is used to calculate the enrichment score (ES) of the sample for a given gene set.
A numeric matrix with association statistics between gene sets vs. samples.
Mauro Castro
data(tniData) ## Not run: #generate a TNI object 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) #compute single-sample GSEA #note: regulons are not required for this function, #as it will assess the samples in the TNI object ES <- tni.annotate.samples(rtni, geneSetList) ## End(Not run)