Calculate gene set correlation

Compute correlation between a foldchange vector/matrix and gene sets

Usage

gset.cor(FC, gset, compute.p = FALSE, use.rank = FALSE)

Arguments

FC

Numeric vector or matrix of (log)foldchanges, with genes as row names

gset

Numeric matrix of gene sets, with genes as row/column names

compute.p

Logical indicating whether to compute p-values

use.rank

Logical indicating whether to rank transform FC before correlation

Value

Named list with components:

• rho - Matrix of correlation coefficients between FC and gset

• p.value - Matrix of p-values for correlation (if compute.p = TRUE)

• q.value - Matrix of FDR adjusted p-values (if compute.p = TRUE)

Details

This function calculates sparse rank correlation between FC and each column of gset using qlcMatrix::corSparse(). It handles missing values in FC by computing column-wise correlations.

P-values are computed from statistical distribution

Examples

if (FALSE) { # \dontrun{
library(playbase)
ranks <- sample(1:10000, 1000, replace = TRUE)
names(ranks) <- replicate(1000, paste(sample(LETTERS, 4, replace = TRUE), collapse = ""))
genesets <- matrix(rnorm(1000 * 20), ncol = 20)
rownames(genesets) <- names(ranks)

gset.rankcor(ranks, genesets, compute.p = TRUE)
} # }