sampleSpecialization: Entropy-based sample specialization

In Accio/BioQC: Detect tissue heterogeneity in expression profiles with gene sets

Description

Entropy-based sample specialization

Usage

sampleSpecialization(mat, norm = TRUE)

Arguments

mat	A matrix (usually an expression matrix), with genes (features) in rows and samples in columns.
norm	Logical, whether the specialization should be normalized by log2(ncol(mat)).

Value

A vector as long as the column number of the input matrix

References

Martinez and Reyes-Valdes (2008) Defining diversity, specialization, and gene specificity in transcriptomes through information theory. PNAS 105(28):9709–9714

See Also

entropy and entropyDiversity

Examples

myMat <- rbind(c(3,4,5),c(6,6,6), c(0,2,4))
sampleSpecialization(myMat)
sampleSpecialization(myMat, norm=TRUE)

myRandomMat <- matrix(runif(1000), ncol=20)
sampleSpecialization(myRandomMat)
sampleSpecialization(myRandomMat, norm=TRUE)

Accio/BioQC documentation built on Jan. 27, 2022, 10:45 p.m.