Generate mask for clusters on 2D dimensional reduction plots

Internally the function rasterizes and smoothes the density plots.

Usage

generateMask(
  dims,
  clusters,
  gridSize = 200,
  expand = 0.005,
  minDensity = lifecycle::deprecated(),
  smoothSigma = NA,
  minSize = 10,
  kernel = lifecycle::deprecated(),
  type = lifecycle::deprecated()
)

Arguments

dims

matrix of point coordinates. Rows are points, columns are dimensions. Only the first two columns are used.

clusters

vector of cluster annotations. Should be the same length as the number of rows in dims.

gridSize

target width and height of the raster used internally

expand

distance used to expand borders, represented as a fraction of sqrt(width*height). Default: 1/200.

minDensity

Deprecated. Doesn't do anything.

smoothSigma

Deprecated. Parameter controlling smoothing and joining close cells into groups, represented as a fraction of sqrt(width*height). Increasing this parameter can help dealing with sparse regions.

minSize

Groups of less than minSize points are ignored, unless it is the only group for a cluster

kernel

Deprecated. Doesn't do anything.

type

Deprecated. Doesn't do anything.

Value

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.

Examples

data("exampleMascarade")
maskTable <- generateMask(dims=exampleMascarade$dims,
                          clusters=exampleMascarade$clusters)
data <- data.frame(exampleMascarade$dims,
                   cluster=exampleMascarade$clusters,
                   exampleMascarade$features)
library(ggplot2)
ggplot(data, aes(x=UMAP_1, y=UMAP_2)) +
    geom_point(aes(color=cluster)) +
    geom_path(data=maskTable, aes(group=group)) +
    coord_fixed() +
    theme_classic()