gene_het: Find the Heterogeneity of a Gene Within a Population

In hwarden162/SCEnt: Single Cell Entropy Analysis of Gene Heterogeneity in Cell Populations

Description

Find the Heterogeneity of a Gene Within a Population

Usage

gene_het(expr, unit = "log2", normalise = TRUE, transpose = FALSE)

Arguments

expr	A vector or matrix of gene expressions. For the matrix, genes should be represented as rows and cells as columns.
unit	The units to be parsed to the entropy function.
normalise	A logical value representing whether the gene frequencies should be normalised into a distribution.
transpose	A logical value representing whether the matrix should be transposed before any calculations are performed.

Value

A vector of the information gained from the gene distribution compared to the uniform distribution. The higher the value more heterogeneous the cell is within the population.

Examples

# Creating Data
gene1 <- c(0, 0, 0, 0, 1, 2, 3)
gene2 <- c(5, 5, 3, 2, 0, 0, 0)
gene3 <- c(2, 0, 2, 1, 3, 0, 1)
gene4 <- c(3, 3, 3, 3, 3, 3, 3)
gene5 <- c(0, 0, 0, 0, 5, 0, 0)
gene_counts <- matrix(c(gene1, gene2, gene3, gene4, gene5), ncol = 5)
rownames(gene_counts) <- paste0("cell", 1:7)
colnames(gene_counts) <- paste0("gene", 1:5)

# Calculating Heterogeneity For Each Gene
gene_het(gene1)
gene_het(gene2)
gene_het(gene3)
gene_het(gene4)
gene_het(gene5)

# Calculating Heterogeneity For a Matrix
gene_het(gene_counts)

hwarden162/SCEnt documentation built on Dec. 20, 2021, 5:52 p.m.