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

eset_stad <- load_data("eset_stad")
#> ℹ Trying mirror 1/4: <https://github.com>
#> ✔ Download complete: "eset_stad"
anno_rnaseq <- load_data("anno_rnaseq")
#> ℹ Trying mirror 1/4: <https://github.com>
#> ✔ Download complete: "anno_rnaseq"
eset <- anno_eset(eset = eset_stad, annotation = anno_rnaseq)
#> ℹ Row number of original eset: 60483
#> ✔ 100% of probes in expression set were annotated
#> ℹ Found 2098 duplicate symbols, using "mean" method
#> ℹ Row number after filtering duplicated gene symbol: 50139
eset_distribution(eset)
#> ✔ Applied log2 transformation
eset_distribution(eset, project = file.path(tempdir(), "ESET"))
#> ✔ Applied log2 transformation