R/generateMaskSeurat.R

In mascarade: Generating Cluster Masks for Single-Cell Dimensional Reduction Plots

#' Generates mask from a Seurat object. Requires `SeuratObject` package.
#'
#' @param object Seurat object
#' @param reduction character vector specifying which reduction to use
#'      (default: `DefaultDimReduc(object)`)
#' @param group.by character vector specifying which field to use for clusters
#'      (default: `"ident"`)
#' @returns data.table with points representing the mask borders.
#'      Each individual border line corresponds to a single level of `group` column.
#'      Cluster assignment is in `cluster` column.
#' @inheritParams generateMask
#' @export
#' @examples
#' # only run if Seurat is installed
#' if (require("Seurat")) {
#'     data("pbmc_small")
#'     maskTable <- generateMaskSeurat(pbmc_small)
#'
#'     library(ggplot2)
#'     # not the best plot, see vignettes for better examples
#'     DimPlot(pbmc_small) +
#'         geom_path(data=maskTable, aes(x=tSNE_1, y=tSNE_2, group=group))
#' }
generateMaskSeurat <- function(object,
                               reduction = NULL,
                               group.by = NULL,
                               gridSize = 200,
                               expand = 0.005,
                               minSize = 10) {
    stopifnot(requireNamespace("SeuratObject", quietly = TRUE))

    if (is.null(reduction)) {
        reduction <- SeuratObject::DefaultDimReduc(object)
    }
    dims <- SeuratObject::Embeddings(object, reduction=reduction)

    if (is.null(group.by)) {
        group.by <- "ident"
    }
    clusters <- SeuratObject::FetchData(object, group.by)[,1]

    maskTable <- generateMask(dims = dims,
                              clusters = clusters,
                              gridSize = gridSize,
                              expand = expand,
                              minSize = minSize)

}