Plot Estimated Gene Means Between Two Datasets — plot_estimated

This function generates a scatter plot comparing gene-wise expression means between two datasets (`estimates_X` and `estimates_Y`) for a specified normalization method. A reference line with slope = 1 is included to help visualize agreement between datasets.

Usage

plot_estimated_means(
  estimates_X,
  estimates_Y,
  method = c("raw", "logcpm", "mle", "map", "libnorm_mle", "libnorm_map"),
  log = TRUE,
  ancestry_X = "Dataset X",
  ancestry_Y = "Dataset Y",
  title = NULL,
  x_label = NULL,
  y_label = NULL,
  point_size = 1
)

Arguments

estimates_X: A list returned by `estimate_params()` for dataset X. Must contain a `means` sublist.
estimates_Y: A list returned by `estimate_params()` for dataset Y. Must contain a `means` sublist.
method: Character. Type of gene-level mean to compare. One of `"raw"` (unadjusted counts), `"libnorm"` (library-normalized counts), or `"logcpm"` (log2 counts per million).
log: Logical. Whether to log10-transform the mean values before plotting. Default is `FALSE`.
ancestry_X: Character. Label used for dataset X in axis titles. Default is `"Dataset X"`.
ancestry_Y: Character. Label used for dataset Y in axis titles. Default is `"Dataset Y"`.
title: Plot title.
x_label: X-axis label.
y_label: Y-axis label.
point_size: Numeric. Size of the scatter plot points. Default is `1`.

Value

A [ggplot2::ggplot()] object showing gene-wise mean comparison.

Examples

if (FALSE) { # \dontrun{
estimates_X <- estimate_params(count_matrix_X)
estimates_Y <- estimate_params(count_matrix_Y)
plot_estimated_means(estimates_X, estimates_Y, method = "libnorm", log = TRUE)
} # }