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Reorder idents by the gene expression

Usage

srt_reorder(
  srt,
  features = NULL,
  reorder_by = NULL,
  layer = "data",
  assay = NULL,
  log = TRUE,
  distance_metric = "euclidean",
  verbose = TRUE
)

Arguments

srt

A Seurat object.

features

A character vector or a named list of features to plot. Features can be gene names in Assay or names of numeric columns in meta.data.

reorder_by

Reorder groups instead of idents.

layer

Which layer to use. Default is data.

assay

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

log

Whether log1p transformation needs to be applied. Default is TRUE.

distance_metric

Metric to compute distance. Default is "euclidean".

verbose

Whether to print the message. Default is TRUE.

Examples

data(pancreas_sub)
pancreas_sub <- standard_scop(pancreas_sub)
#>  [2026-01-27 08:39:00] Start standard scop workflow...
#>  [2026-01-27 08:39:00] Checking a list of <Seurat>...
#> ! [2026-01-27 08:39:00] Data 1/1 of the `srt_list` is "unknown"
#>  [2026-01-27 08:39:00] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on the data 1/1 of the `srt_list`...
#>  [2026-01-27 08:39:03] Perform `Seurat::FindVariableFeatures()` on the data 1/1 of the `srt_list`...
#>  [2026-01-27 08:39:03] Use the separate HVF from srt_list
#>  [2026-01-27 08:39:03] Number of available HVF: 2000
#>  [2026-01-27 08:39:04] Finished check
#>  [2026-01-27 08:39:04] Perform `Seurat::ScaleData()`
#>  [2026-01-27 08:39:04] Perform pca linear dimension reduction
#>  [2026-01-27 08:39:05] Perform `Seurat::FindClusters()` with `cluster_algorithm = 'louvain'` and `cluster_resolution = 0.6`
#>  [2026-01-27 08:39:05] Reorder clusters...
#>  [2026-01-27 08:39:05] Perform umap nonlinear dimension reduction
#>  [2026-01-27 08:39:05] Non-linear dimensionality reduction (umap) using (Standardpca) dims (1-50) as input
#>  [2026-01-27 08:39:10] Non-linear dimensionality reduction (umap) using (Standardpca) dims (1-50) as input
#>  [2026-01-27 08:39:15] Run scop standard workflow completed
pancreas_sub <- srt_reorder(
  pancreas_sub,
  reorder_by = "SubCellType",
  layer = "data"
)