Visualize Expression Set Distribution — eset

Generates boxplots and density plots to analyze the distribution of expression values in an expression set. Useful for quality control and assessing data normalization.

Usage

eset_distribution(eset, quantile = 3, log = TRUE, project = NULL)

Arguments

eset: Expression matrix or data frame with genes in rows and samples in columns.
quantile: Integer specifying the divisor for sampling columns. Default is 3 (samples 1/3 of columns).
log: Logical indicating whether to perform log2 transformation. Default is `TRUE`.
project: Optional output directory path for saving files. If `NULL`, no files are saved. Default is `NULL`.

Value

Invisibly returns `NULL`. If `project` is provided, saves PNG files to disk.

Examples

# Simulate data
set.seed(123)
sim_eset <- matrix(rnorm(1000 * 10, mean = 5, sd = 2), 1000, 10)
rownames(sim_eset) <- paste0("Gene", 1:1000)
colnames(sim_eset) <- paste0("Sample", 1:10)

# Run distribution plot
result <- eset_distribution(sim_eset)
#> ℹ Log2 transformation not necessary (data appears to already be log-scaled)