Annotate single cells using scmap.

Annotate single cells using scmap.

Usage

RunScmap(
  srt_query,
  srt_ref,
  ref_group = NULL,
  query_assay = "RNA",
  ref_assay = "RNA",
  method = "scmapCluster",
  nfeatures = 500,
  threshold = 0.5,
  k = 10,
  verbose = TRUE
)

Arguments

srt_query

An object of class Seurat to be annotated with cell types.

srt_ref

An object of class Seurat storing the reference cells.

ref_group

A character vector specifying the column name in the srt_ref metadata that represents the cell grouping.

query_assay

A character vector specifying the assay to be used for the query data. Default is the default assay of the srt_query object.

ref_assay

A character vector specifying the assay to be used for the reference data. Default is the default assay of the srt_ref object.

method

The method to be used for scmap analysis. Can be any of "scmapCluster" or "scmapCell". Default is "scmapCluster".

nfeatures

The number of top features to be selected. Default is 500.

threshold

The threshold value on similarity to determine if a cell is assigned to a cluster. This should be a value between 0 and 1. Default is 0.5.

k

Number of clusters per group for k-means clustering when method is "scmapCell". Default is 10.

verbose

Whether to print the message. Default is TRUE.

See also

RunKNNPredict, RunKNNMap

Examples

data(panc8_sub)
panc8_sub <- standard_scop(panc8_sub)

genenames <- make.unique(
  thisutils::capitalize(
    rownames(panc8_sub),
    force_tolower = TRUE
  )
)
names(genenames) <- rownames(panc8_sub)
panc8_sub <- RenameFeatures(
  panc8_sub,
  newnames = genenames
)
panc8_sub <- CheckDataMerge(
  panc8_sub,
  batch = "tech"
)[["srt_merge"]]

data(pancreas_sub)
pancreas_sub <- standard_scop(pancreas_sub)
pancreas_sub <- RunScmap(
  srt_query = pancreas_sub,
  srt_ref = panc8_sub,
  ref_group = "celltype",
  method = "scmapCluster"
)
CellDimPlot(
  pancreas_sub,
  group.by = "scmap_annotation"
)

pancreas_sub <- RunScmap(
  srt_query = pancreas_sub,
  srt_ref = panc8_sub,
  ref_group = "celltype",
  method = "scmapCell"
)
CellDimPlot(
  pancreas_sub,
  group.by = "scmap_annotation"
)