Plots features weight as a scatterplot — plot_features_weight

Plots the features weight from a pair of latent dimensions from one or two dimension reduction analysis as a scatterplot.

Usage

plot_features_weight_pair(
  method_output,
  latent_dimensions,
  datasets = NULL,
  features_metric = c("signed_importance", "weight", "importance"),
  include_missing_features = TRUE,
  top_n = 5,
  metric = "geometric",
  label_cols = NULL,
  mo_data = NULL,
  truncate = NULL,
  ncol = NULL,
  label_size = 3
)

Arguments

method_output: A single Integration method output generated via the get_output() function, or a list of two integration method outputs.
latent_dimensions: Character vector of length 2 (if method_output is a single output object), or named list of length 2 (if method_output is a list of two output objects). In the first case, gives the name of the two latent dimensions that should be represented. In the second case, the names of the list should correspond to the names of the methods, and the values should each be a character giving for the corresponding method the name of the latent dimension to display.
datasets: Character vector, names of the datasets for which features weight should be plotted. Default value is NULL, i.e. all relevant datasets are shown.
features_metric: Character, the features metric that should be plotted on the y-axis. Should be one of 'signed_importance' (default value), 'weight' or 'importance'.
include_missing_features: Logical, whether to show the features that were in the input of one method but not the other, when comparing the results of two different integration methods. Default value is TRUE.
top_n: Integer, number of top features (according to the consensus importance metric) to highlight in the plot. Default value is 5.
metric: Character, one of the metrics to use to compute the consensus score. Can be one of 'min', 'max', 'average', 'product', 'l2' (for L2-norm), 'geometric' (for geometric mean) or 'harmonic' (for harmonic mean). Default value is 'geometric'. Names must match those of output_list.
label_cols: Character or named list of character, giving for each dataset the name of the column in the corresponding features metadata to use as label. If one value, will be used for all datasets. If list, the names must correspond to the names of the datasets in mo_data. If a dataset is missing from the list or no value is provided, feature IDs will be used as labels. Alternatively, use feature_id to get the feature IDs as labels.
mo_data: A MultiDataSet object. Only used if label_cols is not NULL.
truncate: Integer, width to which the labels should be truncated (to avoid issues with very long labels in plots). If NULL (default value), no truncation will be performed.
ncol: Integer, number of columns of datasets in the combined plot. Default value is NULL, i.e. will be picked automatically.
label_size: Integer, size of the features label. Default value is 3.

Value

A ggplot.