plotFactorScatters {MOFA} | R Documentation

## Pairwise scatterplots of multiple latent factors

### Description

Scatterplots of the sample values for pair-wise combinations of multiple latent factors.

### Usage

    plotFactorScatters(object, factors = "all", showMissing = TRUE,
      color_by = NULL, name_color = "", shape_by = NULL,
      name_shape = "")

### Arguments

`object` | a `MOFAmodel` object.
`factors` | character vector with the factor name(s), or numeric vector with the index of the factor(s) to use. Default is 'all'
`showMissing` | logical indicating whether to include samples for which `shape_by` or `color_by` is missing
`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.
`name_color` | name for color legend (usually only used if color_by is not a character itself)
`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_shape` | name for shape legend (usually only used if shape_by is not a character itself)

### Details

One of the first steps for the annotation of factors is to visualise and overlap them with known covariates such as phenotypic or clinical data. This method generates multiple scatterplots for pairwise combinations of several latent factors. Similar functions are `plotFactorScatter` for doing single scatter plots and `plotFactorBeeswarm` for doing Beeswarm plots for single factors.

### Value

`ggplot2` object

### Examples

    # Example on the CLL data
    filepath <- system.file("extdata", "CLL_model.hdf5", package = "MOFAdata")
    MOFA_CLL <- loadModel(filepath)
    plotFactorScatters(MOFA_CLL, factors=1:3)
    plotFactorScatters(MOFA_CLL, factors=1:3, color_by= "IGHV")

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

[Package MOFA version 1.0.0 Index]