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Run CellChat analysis

Source: R/RunCellChat.R
RunCellChat.Rd

Run CellChat analysis

Usage

RunCellChat(
  srt,
  group.by,
  species = c("Homo_sapiens", "Mus_musculus", "zebrafish"),
  split.by = NULL,
  annotation_selected = NULL,
  group_column = NULL,
  group_cmp = NULL,
  thresh = 0.05,
  min.cells = 10,
  do.fast = FALSE,
  backend = c("cpp", "r"),
  assay = NULL,
  layer = "data",
  verbose = TRUE
)

Arguments

srt

A Seurat object.

group.by

Name of one or more meta.data columns to group (color) cells by.

species

The species of the data, either "Homo_sapiens", "Mus_musculus", or "zebrafish".

split.by

Name of a column in meta.data column to split plot by. Default is NULL.

annotation_selected

A vector of cell annotations of interest for running the CellChat analysis. If not provided, all cell types will be considered.

group_column

Name of the metadata column in the Seurat object that defines conditions or groups.

group_cmp

A list of pairwise condition comparisons for differential CellChat analysis.

thresh

The threshold for computing centrality scores. Default is 0.05.

min.cells

the minmum number of expressed cells required for the genes that are considered for cell-cell communication analysis. Default is 10.

do.fast

Whether to use CellChat's fast Wilcoxon implementation backed by presto. Set to TRUE only when presto is installed.

backend

Backend used for scop post-processing and unified CCC table aggregation. Upstream CellChat inference is unchanged.

assay

Which assay to use. If NULL, the default assay of the Seurat object will be used.

layer

The layer to use for the expression data. Default is "data".

verbose

Whether to print the message. Default is TRUE.

Value

A Seurat object with CellChat results stored in srt@tools[["CellChat"]].

References

CellChat

See also

CCCHeatmap, CCCStatPlot, CCCNetworkPlot

Examples

data(pancreas_sub)
pancreas_sub <- standard_scop(pancreas_sub)
#> ℹ [2026-07-02 09:26:31] Start standard processing workflow...
#> ℹ [2026-07-02 09:26:32] Checking a list of <Seurat>...
#> ! [2026-07-02 09:26:32] Data 1/1 of the `srt_list` is "unknown"
#> ℹ [2026-07-02 09:26:32] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on 1/1 of `srt_list`...
#> ℹ [2026-07-02 09:26:32] Perform `FindVariableFeatures()` on 1/1 of `srt_list`...
#> ℹ [2026-07-02 09:26:32] Use the separate HVF from `srt_list`
#> ℹ [2026-07-02 09:26:32] Number of available HVF: 2000
#> ℹ [2026-07-02 09:26:32] Finished check
#> ℹ [2026-07-02 09:26:32] Perform `ScaleData()`
#> ℹ [2026-07-02 09:26:32] Perform pca linear dimension reduction
#> ℹ [2026-07-02 09:26:33] Use stored estimated dimensions 1:23 for Standardpca
#> ℹ [2026-07-02 09:26:33] Perform `Seurat::FindClusters()` with `cluster_algorithm = 'louvain'` and `cluster_resolution = 0.6`
#> ℹ [2026-07-02 09:26:33] Reorder clusters...
#> ℹ [2026-07-02 09:26:33] Skip `log1p()` because `layer = data` is not "counts"
#> ℹ [2026-07-02 09:26:33] Perform umap nonlinear dimension reduction
#> ✔ [2026-07-02 09:26:40] Standard processing workflow completed
pancreas_sub <- RunCellChat(
  pancreas_sub,
  group.by = "CellType",
  species = "Mus_musculus"
)
#> ℹ [2026-07-02 09:26:40] Start CellChat analysis
#> Error in loadNamespace(name): there is no package called ‘CellChat’

CCCNetworkPlot(
  pancreas_sub,
  method = "CellChat",
  plot_type = "bipartite"
)
#> Error in get_dataset_object(srt, condition = condition, dataset = dataset): Unable to determine which CellChat object to plot. Please specify
#> `condition`

CCCHeatmap(
  pancreas_sub,
  method = "CellChat",
  plot_type = "heatmap"
)
#> Error in get_dataset_object(srt, condition = condition, dataset = dataset): Unable to determine which CellChat object to plot. Please specify
#> `condition`

CCCStatPlot(
  pancreas_sub,
  method = "CellChat",
  plot_type = "violin",
  top_n = 50
)
#> Error in get_dataset_object(srt, condition = condition, dataset = dataset): Unable to determine which CellChat object to plot. Please specify
#> `condition`