plot_factors {MOFA2} | R Documentation |
Scatterplot of the values of two latent factors.
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 )
object |
a trained |
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 |
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 |
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.
Returns a ggplot2
object
# 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)