tni.annotate.samples {RTN}R Documentation

Annotate samples with external gene set collections.

Description

This function calculates an enrichment score between gene sets and samples.

Usage

tni.annotate.samples(object, geneSetList, minGeneSetSize = 15, 
    exponent = 1, samples=NULL, verbose = TRUE)

Arguments

object

a preprocessed object of class 'TNI' TNI-class.

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).

samples

an optional string vector listing the sample names for which will be computed the GSEA statistics.

verbose

a single logical value specifying to display detailed messages (when verbose=TRUE) or not (when verbose=FALSE).

Details

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.

Value

A numeric matrix with association statistics between gene sets vs. samples.

Author(s)

Mauro Castro

See Also

TNI-class

Examples


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)

[Package RTN version 2.16.0 Index]