RunSlingshot

Runs the Slingshot algorithm on a Seurat object.

Usage

RunSlingshot(
  srt,
  group.by,
  reduction = NULL,
  dims = NULL,
  start = NULL,
  end = NULL,
  prefix = NULL,
  reverse = FALSE,
  align_start = FALSE,
  show_plot = TRUE,
  lineage_palette = "Dark2",
  seed = 11,
  ...
)

Arguments

srt: A Seurat object.
group.by: The variable to group the cells by.
reduction: The reduction technique to use for dimensionality reduction. Default is NULL, which uses the default reduction for the Seurat object.
dims: The dimensions to use for the Slingshot algorithm. Default is NULL, which uses first two dimensions.
start: The starting group for the Slingshot algorithm. Default is NULL.
end: The ending group for the Slingshot algorithm. Default is NULL.
prefix: The prefix to add to the column names of the resulting pseudotime variable. Default is NULL.
reverse: Logical value indicating whether to reverse the pseudotime variable. Default is FALSE.
align_start: Logical value indicating whether to align the starting pseudotime values at the maximum pseudotime. Default is FALSE.
show_plot: Logical value indicating whether to show the dimensionality plot. Default is TRUE.
lineage_palette: The color palette to use for the lineages in the plot. Default is "Dark2".
seed: The random seed to use for reproducibility. Default is 11.
...: Additional arguments to be passed to the slingshot function.

Examples

data("pancreas_sub")
pancreas_sub <- RunSlingshot(
  pancreas_sub,
  group.by = "SubCellType",
  reduction = "UMAP"
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's fill values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's fill values.
#> Warning: Removed 9 rows containing missing values or values outside the scale range
#> (`geom_path()`).
#> Warning: Removed 9 rows containing missing values or values outside the scale range
#> (`geom_path()`).
#> Warning: Removed 13 rows containing missing values or values outside the scale range
#> (`geom_path()`).
#> Warning: Removed 13 rows containing missing values or values outside the scale range
#> (`geom_path()`).

pancreas_sub <- RunSlingshot(
  pancreas_sub,
  group.by = "SubCellType",
  reduction = "PCA",
  dims = 1:10
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's fill values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's fill values.

CellDimPlot(
  pancreas_sub,
  group.by = "SubCellType",
  reduction = "UMAP",
  lineages = paste0("Lineage", 1:2),
  lineages_span = 0.1
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's fill values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's fill values.


# 3D lineage
pancreas_sub <- standard_scop(pancreas_sub)
#> ℹ [2025-07-02 03:06:28] Start standard_scop
#> ℹ [2025-07-02 03:06:28] Checking srt_list...
#> ℹ [2025-07-02 03:06:29] Data 1/1 of the srt_list has been log-normalized.
#> ℹ [2025-07-02 03:06:29] Perform FindVariableFeatures on the data 1/1 of the srt_list...
#> ℹ [2025-07-02 03:06:29] Use the separate HVF from srt_list...
#> ℹ [2025-07-02 03:06:29] Number of available HVF: 2000
#> ℹ [2025-07-02 03:06:30] Finished checking.
#> ℹ [2025-07-02 03:06:30] Perform ScaleData on the data...
#> ℹ [2025-07-02 03:06:30] Perform linear dimension reduction (pca) on the data...
#> ℹ [2025-07-02 03:06:30] linear_reduction(pca) is already existed. Skip calculation.
#> ℹ [2025-07-02 03:06:30] Perform FindClusters (louvain) on the data...
#> ℹ [2025-07-02 03:06:30] Reorder clusters...
#> ! [2025-07-02 03:06:30] Using 'Seurat::AggregateExpression()' to calculate pseudo-bulk data for 'Assay5'.
#> ℹ [2025-07-02 03:06:31] Perform nonlinear dimension reduction (umap) on the data...
#> ℹ [2025-07-02 03:06:31] Non-linear dimensionality reduction(umap) using Reduction(Standardpca, dims:1-50) as input
#> ℹ [2025-07-02 03:06:35] Non-linear dimensionality reduction(umap) using Reduction(Standardpca, dims:1-50) as input
#> ✔ [2025-07-02 03:06:40] Run standard_scop done
#> ℹ [2025-07-02 03:06:40] Elapsed time:11.31 secs
pancreas_sub <- RunSlingshot(
  pancreas_sub,
  group.by = "SubCellType",
  reduction = "StandardpcaUMAP3D"
)
CellDimPlot(
  pancreas_sub,
  group.by = "SubCellType",
  reduction = "UMAP",
  lineages = paste0("Lineage", 1:2),
  lineages_span = 0.1,
  lineages_trim = c(0.05, 0.95)
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's fill values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's fill values.

Usage

Arguments

See also

Examples