Run PAGA analysis

PAGA is a graph-based method used to infer cellular trajectories. This function runs the PAGA analysis on a Seurat object.

Usage

RunPAGA(
  srt = NULL,
  assay_X = "RNA",
  slot_X = "counts",
  assay_layers = c("spliced", "unspliced"),
  slot_layers = "counts",
  adata = NULL,
  group_by = NULL,
  linear_reduction = NULL,
  nonlinear_reduction = NULL,
  basis = NULL,
  n_pcs = 30,
  n_neighbors = 30,
  use_rna_velocity = FALSE,
  vkey = "stochastic",
  embedded_with_PAGA = FALSE,
  paga_layout = "fr",
  threshold = 0.1,
  point_size = 20,
  infer_pseudotime = FALSE,
  root_group = NULL,
  root_cell = NULL,
  n_dcs = 10,
  n_branchings = 0,
  min_group_size = 0.01,
  palette = "Paired",
  palcolor = NULL,
  show_plot = TRUE,
  save = FALSE,
  dpi = 300,
  dirpath = "./",
  fileprefix = "",
  return_seurat = !is.null(srt)
)

Arguments

srt: A Seurat object.
assay_X: Assay to convert as the main data matrix (X) in the anndata object.
slot_X: Slot name for assay_X in the Seurat object.
assay_layers: Assays to convert as layers in the anndata object.
slot_layers: Slot names for the assay_layers in the Seurat object.
adata: An anndata object.
group_by: Variable to use for grouping cells in the Seurat object.
linear_reduction: Linear reduction method to use, e.g., "PCA".
nonlinear_reduction: Non-linear reduction method to use, e.g., "UMAP".
basis: The basis to use for reduction, e.g., "UMAP".
n_pcs: Number of principal components to use for linear reduction. Default is 30.
n_neighbors: Number of neighbors to use for constructing the KNN graph. Default is 30.
use_rna_velocity: Whether to use RNA velocity for PAGA analysis. Default is FALSE.
vkey: The name of the RNA velocity data to use if use_rna_velocity is TRUE. Default is "stochastic".
embedded_with_PAGA: Whether to embed data using PAGA layout. Default is FALSE.
paga_layout: The layout for plotting PAGA graph. See See layout param in scanpy.pl.paga function.
threshold: The threshold for plotting PAGA graph. Edges for weights below this threshold will not draw.
point_size: The point size for plotting.
infer_pseudotime: Whether to infer pseudotime.
root_group: The group to use as the root for pseudotime inference.
root_cell: The cell to use as the root for pseudotime inference.
n_dcs: TThe number of diffusion components to use for pseudotime inference.
n_branchings: Number of branchings to detect.
min_group_size: The minimum size of a group (as a fraction of the total number of cells) to consider it as a potential branching point.
palette: The palette to use for coloring cells.
palcolor: A vector of colors to use as the palette.
show_plot: Whether to show the PAGA plot.
save: Whether to save the PAGA plots.
dpi: The DPI (dots per inch) for saving the PAGA plot.
dirpath: The directory to save the PAGA plots.
fileprefix: The file prefix to use for the PAGA plots.
return_seurat: Whether to return a Seurat object instead of an anndata object. Default is TRUE.

Examples

data("pancreas_sub")
pancreas_sub <- RunPAGA(srt = pancreas_sub, assay_X = "RNA", group_by = "SubCellType", linear_reduction = "PCA", nonlinear_reduction = "UMAP")
#> 'misc' slot is not converted.
#> 'tools' slot is not converted.
#> Error in slot(object = object, name = "features")[[layer]] <- features: more elements supplied than there are to replace
CellDimPlot(pancreas_sub, group.by = "SubCellType", reduction = "draw_graph_fr")

PAGAPlot(pancreas_sub, reduction = "UMAP")
#> Error in PAGAPlot(pancreas_sub, reduction = "UMAP"): Cannot find the paga result.
CellDimPlot(pancreas_sub, group.by = "SubCellType", reduction = "UMAP", paga = pancreas_sub@misc$paga)


pancreas_sub <- RunPAGA(
  srt = pancreas_sub, group_by = "SubCellType", linear_reduction = "PCA", nonlinear_reduction = "UMAP",
  embedded_with_PAGA = TRUE, infer_pseudotime = TRUE, root_group = "Ductal"
)
#> 'misc' slot is not converted.
#> 'tools' slot is not converted.
#> Error in slot(object = object, name = "features")[[layer]] <- features: more elements supplied than there are to replace
head(pancreas_sub[[]])
#>                     orig.ident nCount_RNA nFeature_RNA     S_score   G2M_score nCount_spliced nFeature_spliced
#> CAGCCGAAGCGATATA SeuratProject      10653         3295  0.33188155  0.54532743          10653             3295
#> AGTGTCATCGCCGTGA SeuratProject       4596         2053 -0.07156909 -0.08865353           4596             2053
#> GATGAAAAGTTGTAGA SeuratProject      14091         3864  0.08940628  0.77610326          14091             3864
#> CACAGTACATCCGTGG SeuratProject       5484         2510 -0.25927997 -0.25941831           5484             2510
#> CGGAGCTCATTGGGCC SeuratProject       7357         2674 -0.11764368  0.46237856           7357             2674
#> AGAGCTTGTGTGACCC SeuratProject       6498         2516 -0.11406432 -0.17830831           6498             2516
#>                  nCount_unspliced nFeature_unspliced      CellType   SubCellType Phase
#> CAGCCGAAGCGATATA             1587               1063        Ductal        Ductal   G2M
#> AGTGTCATCGCCGTGA             1199                803 Pre-endocrine Pre-endocrine    G1
#> GATGAAAAGTTGTAGA             2166               1379   Ngn3 low EP   Ngn3 low EP   G2M
#> CACAGTACATCCGTGG             1339                859     Endocrine          Beta    G1
#> CGGAGCTCATTGGGCC              976                745        Ductal        Ductal   G2M
#> AGAGCTTGTGTGACCC              822                591        Ductal        Ductal    G1
names(pancreas_sub@reductions)
#> [1] "PCA"  "UMAP"
FeatureDimPlot(pancreas_sub, features = "dpt_pseudotime", reduction = "PAGAUMAP2D")
#> Warning: dpt_pseudotime are not in the features of srt.
#> Error in FeatureDimPlot(pancreas_sub, features = "dpt_pseudotime", reduction = "PAGAUMAP2D"): There are no valid features present.
PAGAPlot(pancreas_sub, reduction = "PAGAUMAP2D")
#> Error in PAGAPlot(pancreas_sub, reduction = "PAGAUMAP2D"): Cannot find the paga result.
CellDimPlot(pancreas_sub, group.by = "SubCellType", reduction = "PAGAUMAP2D", paga = pancreas_sub@misc$paga)

Usage

Arguments

See also

Examples