plot.COMPASSResult {COMPASS} | R Documentation

## Plot a COMPASSResult

### Description

This function can be used to visualize the mean probability of response; that is, the probability that there is a difference in response between samples subjected to the 'treatment' condition, and samples subjected to the 'control' condition.

### Usage

    ## S3 method for class 'COMPASSResult'
    plot(x, y, subset = NULL, threshold = 0.01,
      minimum_dof = 1, maximum_dof = Inf, must_express = NULL,
      row_annotation, palette = colorRampPalette(brewer.pal(10,
      "Purples"))(20), show_rownames = FALSE, show_colnames = FALSE,
      measure = NULL, order_by = FunctionalityScore,
      order_by_max_functionality = TRUE, markers = NULL, ...)

### Arguments

`x` | An object of class `COMPASSResult`.
`y` | This argument gets passed to `row_annotation`, if `row_annotation` is missing. It can be used to group rows (individuals) by different conditions as defined in the metadata.
`subset` | An R expression, evaluated within the metadata, used to determine which individuals should be kept.
`threshold` | A numeric threshold for filtering under-expressed categories. Any categories with mean score < `threshold` are removed.
`minimum_dof` | The minimum degree of functionality for the categories to be plotted.
`maximum_dof` | The maximum degree of functionality for the categories to be plotted.
`must_express` | A character vector of markers that should be included in each subset plotted. For example, `must_express=c("TNFa & IFNg")` says we include only subsets that are positive for both `TNFa` or `IFNg`, while `must_express=c("TNFa", "IFNg")` says we should keep subsets which are positive for either `TNFa` or `IFNg`.
`row_annotation` | A vector of names, pulled from the metadata, to be used for row annotation.
`palette` | The colour palette to be used.
`show_rownames` | Boolean; if `TRUE` we display row names (ie, the individual ids).
`show_colnames` | Boolean; if `TRUE` we display column names (ie, the column name associated with a cytokine; typically not needed)
`measure` | Optional. By default, we produce a heatmap of the mean gammas produced in a model fit. We can override this by supplying a matrix of suitable dimension as well; these can be generated with the `Posterior*` functions – see `Posterior` for examples.
`order_by` | Order rows within a group. This should be a function; e.g. `FunctionalityScore`, `mean`, `median`, and so on. Set this to `NULL` to preserve the original ordering of the data.
`order_by_max_functionality` | Order columns by functionality within each degree subset. to `TRUE`.
`markers` | specifies a subset of markers to plot. default is NULL, which means all markers.
`...` | Optional arguments passed to `pheatmap`.

### Value

The plot as a `grid` object (`grob`). It can be redrawn with e.g. `grid::grid.draw()`.

### Examples

    ## visualize the mean probability of reponse
    plot(CR)

    ## visualize the proportion of cells belonging to a category
    plot(CR, measure=PosteriorPs(CR))

[Package COMPASS version 1.27.0 Index]