plot_top_weights {MOFA2} | R Documentation

## Plot top weights

### Description

Plot top weights for a given factor and view.

### Usage

    plot_top_weights(
      object,
      view = 1,
      factors = 1,
      nfeatures = 10,
      abs = TRUE,
      scale = TRUE,
      sign = "all"
    )

### Arguments

`object` | a trained `MOFA` object.
`view` | a string with the view name, or an integer with the index of the view.
`factors` | a character string with factors names, or an integer vector with factors indices.
`nfeatures` | number of top features to display. Default is 10
`abs` | logical indicating whether to use the absolute value of the weights (Default is FALSE).
`scale` | logical indicating whether to scale all weights from -1 to 1 (or from 0 to 1 if abs=TRUE). Default is TRUE.
`sign` | can be 'positive', 'negative' or 'all' to show only positive, negative or all weights, respectively. Default is 'all'.

### Details

An important step to annotate factors is to visualise the corresponding feature weights.
This function displays the top features with highest loading whereas the function `plot_top_weights` plots all weights for a given latent factor and view.
Importantly, the weights of the features within a view have relative values and they should not be interpreted in an absolute scale. Therefore, for interpretability purposes we always recommend to scale the weights with `scale=TRUE`.

### Value

Returns a `ggplot2` object

### Examples

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

    # Plot top weights for Factors 1 and 2 and View 1
    plot_top_weights(model, view = 1, factors = c(1,2))

    # Do not take absolute value
    plot_weights(model, abs = FALSE)

[Package MOFA2 version 1.4.0 Index]