plot_factors: Scatterplots of two factor values

In MOFA2: Multi-Omics Factor Analysis v2

Description

Scatterplot of the values of two latent factors.

Usage

plot_factors(
  object,
  factors = c(1, 2),
  groups = "all",
  show_missing = TRUE,
  scale = FALSE,
  color_by = NULL,
  shape_by = NULL,
  color_name = NULL,
  shape_name = NULL,
  dot_size = 1.5,
  alpha = 1,
  legend = TRUE,
  stroke = NULL,
  return_data = FALSE
)

Arguments

object	a trained MOFA object.
factors	a vector of length two with the factors to plot. Factors can be specified either as a characters
groups	character vector with the groups names, or numeric vector with the indices of the groups of samples to use, or "all" to use samples from all groups.
show_missing	logical indicating whether to include samples for which shape_by or color_by is missing
scale	logical indicating whether to scale factor values.
color_by	specifies groups or values used to color the samples. This can be either: (1) a character giving the name of a feature present in the training data. (2) a character giving the name of a column present in the sample metadata. (3) a vector of the name length as the number of samples specifying discrete groups or continuous numeric values.
shape_by	specifies groups or values used to shape the samples. This can be either: (1) a character giving the name of a feature present in the training data, (2) a character giving the name of a column present in the sample metadata. (3) a vector of the same length as the number of samples specifying discrete groups.
color_name	name for color legend.
shape_name	name for shape legend.
dot_size	numeric indicating dot size (default is 1.5).
alpha	numeric indicating dot transparency (default is 1).
legend	logical indicating whether to add legend.
stroke	numeric indicating the stroke size (the black border around the dots, default is NULL, infered automatically).
return_data	logical indicating whether to return the data frame to plot instead of plotting

Details

One of the first steps for the annotation of factors is to visualise and group/color them using known covariates such as phenotypic or clinical data. This method generates a single scatterplot for the combination of two latent factors. TO-FINISH... plot_factors for doing Beeswarm plots for factors.

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)

# Scatterplot of factors 1 and 2
plot_factors(model, factors = c(1,2))

# Shape dots by a column in the metadata
plot_factors(model, factors = c(1,2), shape_by="group")

# Scale factor values from -1 to 1
plot_factors(model, factors = c(1,2), scale = TRUE)

MOFA2 documentation built on Nov. 8, 2020, 7:28 p.m.