plot_variance_explained {MOFA2} | R Documentation

## Plot variance explained by the model

### Description

plots the variance explained by the MOFA factors across different views and groups, as specified by the user. Consider using cowplot::plot_grid(plotlist = ...) to combine the multiple plots that this function generates.

### Usage

    plot_variance_explained(
      object,
      x = "view",
      y = "factor",
      split_by = NA,
      plot_total = FALSE,
      factors = "all",
      min_r2 = 0,
      max_r2 = NULL,
      legend = TRUE,
      use_cache = TRUE,
      ...
    )

### Arguments

`object` | a `MOFA` object
`x` | character specifying the dimension for the x-axis ("view", "factor", or "group").
`y` | character specifying the dimension for the y-axis ("view", "factor", or "group").
`split_by` | character specifying the dimension to be faceted ("view", "factor", or "group").
`plot_total` | logical value to indicate if to plot the total variance explained (for the variable in the x-axis)
`factors` | character vector with a factor name(s), or numeric vector with the index(es) of the factor(s). Default is "all".
`min_r2` | minimum variance explained for the color scheme (default is 0).
`max_r2` | maximum variance explained for the color scheme.
`legend` | logical indicating whether to add a legend to the plot (default is TRUE).
`use_cache` | logical indicating whether to use cache (default is TRUE)
`...` | extra arguments to be passed to `calculate_variance_explained`

### Value

A list of `ggplot` objects (if `plot_total` is TRUE) or a single `ggplot` object

### Examples

    # Using an existing trained model on simulated data
    file <- system.file("extdata", "model.hdf5", package = "MOFA2")
    model <- load_model(file)

    # Calculate variance explained (R2)
    r2 <- calculate_variance_explained(model)

    # Plot variance explained values (view as x-axis, and factor as y-axis)
    plot_variance_explained(model, x="view", y="factor")

    # Plot variance explained values (view as x-axis, and group as y-axis)
    plot_variance_explained(model, x="view", y="group")

    # Plot variance explained values for factors 1 to 3
    plot_variance_explained(model, x="view", y="group", factors=1:3)

    # Scale R2 values
    plot_variance_explained(model, max_r2=0.25)

[Package MOFA2 version 1.0.1 Index]