baldur (version 0.0.4)

lgmr_plotting: Visualization of LGMR models

Description

Options to plot the LGMR model. plot_lgmr_regression will plot the data colored by the amount of latent trend they have as well as the two extreme regression cases when \(\theta\) is zero or one. plot_regression_field will plot the local regression trend for each data point as a vector field and color the vector based on the derivative at the mean of the peptide.

Usage

plot_lgmr_regression(model)
plot_regression_field(model, n = 10, rng = 10)

Value

A ggplot object

Arguments

model

An LGMR model object

n

Number of interpolation points for each peptides regression

rng

The proportional range of each peptides regression. E.g., a value of 10 will make each line span 1 % of the x-axis.

Examples

#' # Define design matrix
design <- model.matrix(~ 0 + factor(rep(1:2, each = 3)))
colnames(design) <- paste0("ng", c(50, 100))

# \donttest{
# Normalize data, calculate M-V trend, and fit LGMR model
yeast_lgmr <- yeast %>%
    # Remove missing values
    tidyr::drop_na() %>%
    # Normalize
    psrn("identifier") %>%
    # Add the mean-variance trends
    calculate_mean_sd_trends(design) %>%
    # Fit the model
    fit_lgmr("identifier")
# Print everything except thetas
print(yeast_lgmr, pars = c("coefficients", "auxiliary"))
# Extract the mean of the model parameters posterior
yeast_lgmr_pars <- coef(yeast_lgmr, pars = 'all', simplify = TRUE)
plot_lgmr_regression(yeast_lgmr)
plot_regression_field(yeast_lgmr)
# }