Description Usage Arguments Details Value Author(s) See Also Examples
This function calculates an enrichment score between gene sets and samples.
1 2 | 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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | 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)
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