View source: R/SCP-cell_annotation.R
RunScmap | R Documentation |
Annotate single cells using scmap.
RunScmap(
srt_query,
srt_ref,
ref_group = NULL,
query_assay = "RNA",
ref_assay = "RNA",
method = "scmapCluster",
nfeatures = 500,
threshold = 0.5,
k = 10
)
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. Defaults to the default assay of the 'srt_query' object. |
ref_assay |
A character vector specifying the assay to be used for the reference data. Defaults to the default assay of the 'srt_ref' object. |
method |
The method to be used for scmap analysis. Can be any of "scmapCluster" or "scmapCell". The default value is "scmapCluster". |
nfeatures |
The number of top features to be selected. The default value 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. The default value is 0.5. |
k |
Number of clusters per group for k-means clustering when method is "scmapCell". |
data("panc8_sub")
# Simply convert genes from human to mouse and preprocess the data
genenames <- make.unique(capitalize(rownames(panc8_sub), force_tolower = TRUE))
panc8_sub <- RenameFeatures(panc8_sub, newnames = genenames)
panc8_sub <- check_srtMerge(panc8_sub, batch = "tech")[["srtMerge"]]
# Annotation
data("pancreas_sub")
pancreas_sub <- Standard_SCP(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")
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