This function generates a projection plot, which can be used to compare two groups of cells in a dimensionality reduction space.
Usage
ProjectionPlot(
srt_query,
srt_ref,
query_group = NULL,
ref_group = NULL,
query_reduction = "ref.embeddings",
ref_reduction = srt_query[[query_reduction]]@misc[["reduction.model"]] %||% NULL,
query_param = list(palette = "Set1", cells.highlight = TRUE),
ref_param = list(palette = "Paired"),
xlim = NULL,
ylim = NULL,
pt.size = 0.8,
stroke.highlight = 0.5
)Arguments
- srt_query
An object of class Seurat storing the query group cells.
- srt_ref
An object of class Seurat storing the reference group cells.
- query_group
The grouping variable for the query group cells.
- ref_group
The grouping variable for the reference group cells.
- query_reduction
The name of the reduction in the query group cells.
- ref_reduction
The name of the reduction in the reference group cells.
- query_param
A list of parameters for customizing the query group plot. Available parameters: palette (color palette for groups) and cells.highlight (whether to highlight cells).
- ref_param
A list of parameters for customizing the reference group plot. Available parameters: palette (color palette for groups) and cells.highlight (whether to highlight cells).
- xlim
The x-axis limits for the plot. If not provided, the limits will be calculated based on the data.
- ylim
The y-axis limits for the plot. If not provided, the limits will be calculated based on the data.
- pt.size
The size of the points in the plot.
- stroke.highlight
The size of the stroke highlight for cells.
Examples
data(panc8_sub)
srt_ref <- panc8_sub[, panc8_sub$tech != "fluidigmc1"]
srt_query <- panc8_sub[, panc8_sub$tech == "fluidigmc1"]
srt_ref <- integration_scop(
srt_ref,
batch = "tech",
integration_method = "Seurat"
)
#> ℹ [2025-09-20 13:24:45] Run Seurat integration...
#> ℹ [2025-09-20 13:24:45] Spliting `srt_merge` into `srt_list` by column "tech"...
#> ℹ [2025-09-20 13:24:46] Checking a list of <Seurat> object...
#> ! [2025-09-20 13:24:46] Data 1/4 of the `srt_list` is "unknown"
#> ℹ [2025-09-20 13:24:46] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on the data 1/4 of the `srt_list`...
#> ℹ [2025-09-20 13:24:47] Perform `Seurat::FindVariableFeatures()` on the data 1/4 of the `srt_list`...
#> ! [2025-09-20 13:24:47] Data 2/4 of the `srt_list` is "unknown"
#> ℹ [2025-09-20 13:24:47] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on the data 2/4 of the `srt_list`...
#> ℹ [2025-09-20 13:24:49] Perform `Seurat::FindVariableFeatures()` on the data 2/4 of the `srt_list`...
#> ! [2025-09-20 13:24:49] Data 3/4 of the `srt_list` is "unknown"
#> ℹ [2025-09-20 13:24:49] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on the data 3/4 of the `srt_list`...
#> ℹ [2025-09-20 13:24:51] Perform `Seurat::FindVariableFeatures()` on the data 3/4 of the `srt_list`...
#> ! [2025-09-20 13:24:51] Data 4/4 of the `srt_list` is "unknown"
#> ℹ [2025-09-20 13:24:51] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on the data 4/4 of the `srt_list`...
#> ℹ [2025-09-20 13:24:53] Perform `Seurat::FindVariableFeatures()` on the data 4/4 of the `srt_list`...
#> ℹ [2025-09-20 13:24:53] Use the separate HVF from srt_list
#> ℹ [2025-09-20 13:24:53] Number of available HVF: 2000
#> ℹ [2025-09-20 13:24:54] Finished check
#> ℹ [2025-09-20 13:24:55] Perform FindIntegrationAnchors
#> Warning: Different features in new layer data than already exists for scale.data
#> Warning: Different features in new layer data than already exists for scale.data
#> Warning: Different features in new layer data than already exists for scale.data
#> Warning: Different features in new layer data than already exists for scale.data
#> Warning: The `slot` argument of `SetAssayData()` is deprecated as of SeuratObject 5.0.0.
#> ℹ Please use the `layer` argument instead.
#> ℹ The deprecated feature was likely used in the Seurat package.
#> Please report the issue at <https://github.com/satijalab/seurat/issues>.
#> ℹ [2025-09-20 13:25:15] Perform integration(Seurat)
#> Warning: Layer counts isn't present in the assay object; returning NULL
#> Warning: Different cells in new layer data than already exists for scale.data
#> Warning: Layer counts isn't present in the assay object; returning NULL
#> Warning: Different cells in new layer data than already exists for scale.data
#> Warning: Layer counts isn't present in the assay object; returning NULL
#> ℹ [2025-09-20 13:25:23] Perform ScaleData
#> ℹ [2025-09-20 13:25:23] Perform linear dimension reduction ("pca")
#> ℹ [2025-09-20 13:25:24] Perform FindClusters ("louvain")
#> ℹ [2025-09-20 13:25:24] Reorder clusters...
#> ! [2025-09-20 13:25:24] Using `Seurat::AverageExpression()` to calculate pseudo-bulk data for <Assay>
#> ℹ [2025-09-20 13:25:24] Perform nonlinear dimension reduction (umap)
#> ℹ [2025-09-20 13:25:24] Non-linear dimensionality reduction (umap) using (Seuratpca) dims (1-11) as input
#> ℹ [2025-09-20 13:25:28] Non-linear dimensionality reduction (umap) using (Seuratpca) dims (1-11) as input
#> ✔ [2025-09-20 13:25:34] Run Seurat integration done
CellDimPlot(
srt_ref,
group.by = c("celltype", "tech")
)
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's fill values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's fill values.
# Projection
srt_query <- RunKNNMap(
srt_query = srt_query,
srt_ref = srt_ref,
ref_umap = "SeuratUMAP2D"
)
#> ℹ [2025-09-20 13:25:34] Use the features to calculate distance metric
#> Error in CheckDataType(data = GetAssayData5(srt_query, layer = "data", assay = query_assay, verbose = FALSE)): argument "object" is missing, with no default
ProjectionPlot(
srt_query = srt_query,
srt_ref = srt_ref,
query_group = "celltype",
ref_group = "celltype"
)
#> Error in srt_query[[query_reduction]]: ‘ref.embeddings’ not found in this Seurat object
#>