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Plots sample scores against covariate

Source: R/output_plot.R
plot_samples_score_covariate.Rd

Plots the samples score from the result of an integration method against a covariate from the samples metadata.

Usage

plot_samples_score_covariate(
  method_output,
  mo_data,
  covariate,
  latent_dimensions = NULL,
  colour_by = NULL,
  shape_by = NULL,
  point_alpha = 1,
  add_se = TRUE,
  add_boxplot = TRUE,
  ncol = NULL
)

Arguments

method_output

Integration method output generated via the get_output() function.

mo_data

A MultiDataSet object (will be used to extract samples information).

covariate

Character, name of column in one of the samples metadata tables from mo_data to use as x-axis in the plot.

latent_dimensions

Character vector giving the latent dimensions to display. Default value is NULL, i.e. all latent dimensions will be shown.

colour_by

Character, name of column in one of the samples metadata tables from mo_data to use to colour the samples in the plot. Default value is NULL.

shape_by

Character, name of column in one of the samples metadata tables from mo_data to use as shape for the samples in the plot. Default value is NULL.

point_alpha

Numeric between 0 and 1, the opacity of the points in the plot (with 1 = fully opaque, and 0 = fully transparent). Default value is 1.

add_se

Logical, should a confidence interval be drawn around the smoothing curves for numerical covariates? Default value is TRUE.

add_boxplot

Logical, should a boxplot be drawn on top of the points for categorical covariates? Default value is TRUE.

ncol

Integer, number of columns in the faceted plot. Default value is NULL.

Value

a ggplot.

Details

If the covariate is numeric, the function creates a scatter plot, with a loess curve to summarise the trend between the covariate and the samples score. If colour_by is used, and the corresponding variable is numeric, the loess curve will not take into account this variable. If instead the colour_by variable is a character or factor, a loess curve will be fitted separately for each category.

If the covariate is not numeric, the function creates a violin/boxplot. If colour_by is used, and the corresponding variable is numeric, the violins and boxplots will not take into account this variable. If instead the colour_by variable is a character or factor, a separate violin and boxplot will be drawn for each category.