VAM (version 0.5.2)

vamForCollection: VAM method for multiple gene sets

Description

Executes the Variance-adjusted Mahalanobis (VAM) method (vam) on multiple gene sets, i.e., a gene set collection.

Usage

vamForCollection(gene.expr, gene.set.collection, tech.var.prop, 
        center=FALSE, gamma=TRUE)

Arguments

gene.expr

An n x p matrix of gene expression values for n cells and p genes.

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.

tech.var.prop

See description in vam

center

See description in vam

gamma

See description in vam

Value

A list containing two elements:

• "cdf.value": n x m matrix of 1 minus the one-sided p-values for the m gene sets and n cells.

• "distance.sq": n x m matrix of squared adjusted Mahalanobis distances for the m gene sets and n cells.

See Also

vam,vamForSeurat

Examples

# NOT RUN {
    # Simulate Poisson expression data for 10 genes and 10 cells
    gene.expr=matrix(rpois(100, lambda=2), nrow=10)
    # Simulate technical variance proportions
    tech.var.prop=runif(10)
    # Define a collection with two disjoint sets that span the 10 genes
    collection=list(set1=1:5, set2=6:10)    
    # Execute VAM on both sets using default values for center and gamma
    vamForCollection(gene.expr=gene.expr, gene.set.collection=collection,
        tech.var.prop=tech.var.prop)
# }