RepeatedHighDim (version 2.4.0)

scTrimClust: scTrimClust: Cluster visualization with alpha hull-based outlier detection

Description

Visualizes cell clusters in low-dimensional space (t-SNE, UMAP, etc.) and identifies/removes potential outliers based on their distance from cluster alpha hulls.

Usage

scTrimClust(
  object,
  dims = c(1, 2),
  cells = NULL,
  cols = NULL,
  pt.size = NULL,
  reduction = NULL,
  group.by = NULL,
  split.by = NULL,
  shape.by = NULL,
  order = NULL,
  shuffle = FALSE,
  seed = 1,
  label = FALSE,
  label.size = 4,
  label.color = "black",
  label.box = FALSE,
  repel = FALSE,
  alpha = 1,
  stroke.size = NULL,
  cells.highlight = NULL,
  cols.highlight = "#DE2D26",
  sizes.highlight = 1,
  na.value = "grey50",
  ncol = NULL,
  combine = TRUE,
  raster = NULL,
  raster.dpi = c(512, 512),
  add.alpha.hull = TRUE,
  hull.alpha = 2,
  hull.color = NULL,
  hull.size = 0.5,
  outlier.quantile = 0.4,
  remove.outliers = FALSE,
  outlier.alpha = 0.1,
  outlier.color = NULL,
  outlier.colors = NULL,
  outline.color = NULL,
  outline.size = 0.5,
  outline.alpha = 1,
  outline.outliers = FALSE
)

Value

A list containing:

• plot: ggplot object of the visualization with hulls and highlighted outliers

• object: Modified Seurat object with outliers removed (if remove.outliers=TRUE)

• outlier_coords: Dataframe containing coordinates of outlier cells, their IDs and cluster assignments

• hull_info: List containing alpha hull geometries (if add.alpha.hull=TRUE)

Arguments

object

A Seurat object containing dimensionality reduction results.

dims

Integer vector of length 2 specifying which dimensions to plot (e.g., c(1, 2)).

cells

Vector of cells to include (NULL uses all cells).

cols

Vector of colors for clusters.

pt.size

Point size for cells.

reduction

Name of dimensionality reduction to use (e.g., "umap", "tsne").

group.by

Metadata column to group cells by (default: 'ident' uses cluster IDs).

split.by

Metadata column to split plots by (creates multiple facets).

shape.by

Metadata column to determine point shapes.

order

Vector specifying order to plot cells (affects z-ordering).

shuffle

Logical to randomly shuffle plotting order.

seed

Random seed for reproducibility when shuffle=TRUE.

label

Logical to add cluster labels.

label.size

Size of cluster labels.

label.color

Color of cluster labels.

label.box

Logical to add background box to labels.

repel

Logical to use ggrepel for label placement.

alpha

Transparency level for points (0-1).

stroke.size

Size of point borders.

cells.highlight

Specific cells to highlight.

cols.highlight

Color(s) for highlighted cells.

sizes.highlight

Size(s) for highlighted cells.

na.value

Color for NA values.

ncol

Number of columns for faceted plots.

combine

Logical to combine multiple plots into one.

raster

Logical to rasterize points (for large datasets).

raster.dpi

Resolution for rasterized points.

add.alpha.hull

Logical to compute and plot alpha hulls.

hull.alpha

Alpha parameter for hull calculation. Higher values produce smoother hulls that encompass more cells (default: 2).

hull.color

Color of the alpha hull lines (default: Null = same color as cluster points).

hull.size

Thickness of the alpha hull lines (default: 0.5).

outlier.quantile

Quantile threshold (0-1) for outlier detection based on hull distance. Cells with distances below this quantile are considered outliers (default: 0.4).

remove.outliers

Logical - whether to remove outliers from the returned Seurat object (default: FALSE).

outlier.alpha

Transparency level for outlier points (0-1; default: 0.1).

outlier.color

Single color to use for all outlier points. If NULL, uses cluster colors.

outlier.colors

A named vector of colors to be assigned to outliers.If NULL, uses cluster colors.

outline.color

Color for the outline of points. If NULL, no outline is added.

outline.size

Thickness of the outline around points (default: 0.5).

outline.alpha

Transparency of the outline around points (default: 1).

outline.outliers

Logical whether to add outlines to outlier points (default: FALSE).

Examples

if (FALSE) {

scTrimClust(RepeatedHighDim:::seurat_obj,reduction = 'tsne',
group.by = 'CellType',
hull.alpha = 2,
remove.outliers = FALSE,
outlier.quantile = 0.2,
outlier.alpha = 0.3,
outlier.color = "red",
pt.size = 5,
outline.color = "black",
outline.outliers = TRUE)

# second example with custom outlier col per cluster

scTrimClust(RepeatedHighDim:::seurat_obj,reduction = 'tsne',
group.by = 'CellType',
hull.alpha = 2,
remove.outliers = FALSE,
outlier.quantile = 0.2,
outlier.alpha = 0.3,
outlier.colors = c('TypeA'="black",
'TypeB'='violet','TypeC' ='pink'),
pt.size = 5,
outline.color = "black",
outline.outliers = TRUE)$plot

}