TPAC (version 0.3.0)

tpacForCollection: TPAC method for multiple gene sets

Description

Executes the TPAC (tissue-adjusted pathway analysis for cancer) method (tpac) on multiple gene sets, i.e., a gene set collection.

Usage

tpacForCollection(gene.expr, mean.expr, tissue.specificity, gene.set.collection)

Value

A list containing two elements:

• s.pos: n x m matrix of TPAC scores computed using the positive squared adjusted Mahalanobis distances.

• s.neg: n x m matrix of TPAC scores computed using the negative squared adjusted Mahalanobis distances.

• s: n x m matrix of TPAC scores computed using the sum of the positive and negative squared adjusted Mahalanobis distances.

Arguments

gene.expr

See description in tpac

mean.expr

See description in tpac

tissue.specificity

See description in tpac

gene.set.collection

List of m gene sets for which scores are computed. Each element in the list corresponds to a gene set and the list element is a vector of indices for the genes in the set. The index value is defined relative to the order of genes in the gene.expr matrix. Gene set names should be specified as list names.

See Also

tpac,tpacForCancer

Examples

    # Simulate Gaussian expression data for 10 genes and 10 samples
    gene.expr=matrix(rnorm(100), nrow=10)
    # Use 0 as mean.expr 
    mean.expr=rep(0,10)
    # Simulate tissue-specific weights
    tissue.specificity = runif(10, min=0.5, max=1.5)
    # Define a collection with two disjoint sets that span the 10 genes
    collection=list(set1=1:5, set2=6:10)    
    # Execute TPAC on both sets
    tpacForCollection(gene.expr=gene.expr, mean.expr=mean.expr,
        tissue.specificity=tissue.specificity, gene.set.collection=collection)