plotFactorScatter: Scatterplot of two latent factors
In bioFAM/MOFA: Multi-Omics Factor Analysis (MOFA)

Description Usage Arguments Details Value Examples

Scatterplot of the values of two latent factors.

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plotFactorScatter(object, factors, color_by = NULL, shape_by = NULL,
  name_color = "", name_shape = "", dot_size = 1.5, dot_alpha = 1,
  showMissing = TRUE)

`object`	a trained `MOFAmodel` object.
`factors`	a vector of length two with the factors to plot. Factors can be specified either as a characters using the factor names, or as numeric with the index of the factors
`color_by`	specifies groups or values used to color the samples. This can be either a character giving the name of a feature present in the training data, a character giving the same of a covariate (only if using `MultiAssayExperiment` as input), or a vector of the same 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 a character giving the name of a feature present in the training data, a character giving the same of a covariate (only if using `MultiAssayExperiment` as input), or a vector of the same length as the number of samples specifying discrete groups.
`name_color`	name for color legend.
`name_shape`	name for shape legend.
`dot_size`	dot size (default is 1.5).
`dot_alpha`	dot transparency (default is 1.0, no transparency).
`showMissing`	logical indicating whether to include samples for which `shape_by` or `color_by` is missing.

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. Similar functions are plotFactorScatters for doing multiple scatter plots and plotFactorBeeswarm for doing Beeswarm plots for single factors.

Returns a ggplot2 object

# Example on the CLL data
filepath <- system.file("extdata", "CLL_model.hdf5", package = "MOFAdata")
MOFA_CLL <- loadModel(filepath)
plotFactorScatter(MOFA_CLL, factors=1:2)
plotFactorScatter(MOFA_CLL, factors=1:2, color_by= "IGHV", shape_by="trisomy12", showMissing=FALSE)

# Example on the scMT data
filepath <- system.file("extdata", "scMT_model.hdf5", package = "MOFAdata")
MOFA_scMT <- loadModel(filepath)
plotFactorScatter(MOFA_scMT, factors=c(1,3))