Project query data to the reference dimensional reduction

ProjectCellEmbeddings(query, ...)

# S3 method for Seurat
ProjectCellEmbeddings(
  query,
  reference,
  query.assay = NULL,
  reference.assay = NULL,
  reduction = "pca",
  dims = 1:50,
  normalization.method = c("LogNormalize", "SCT"),
  scale = TRUE,
  verbose = TRUE,
  nCount_UMI = NULL,
  feature.mean = NULL,
  feature.sd = NULL,
  ...
)

# S3 method for Assay
ProjectCellEmbeddings(
  query,
  reference,
  reference.assay = NULL,
  reduction = "pca",
  dims = 1:50,
  scale = TRUE,
  normalization.method = NULL,
  verbose = TRUE,
  nCount_UMI = NULL,
  feature.mean = NULL,
  feature.sd = NULL,
  ...
)

# S3 method for SCTAssay
ProjectCellEmbeddings(
  query,
  reference,
  reference.assay = NULL,
  reduction = "pca",
  dims = 1:50,
  scale = TRUE,
  normalization.method = NULL,
  verbose = TRUE,
  nCount_UMI = NULL,
  feature.mean = NULL,
  feature.sd = NULL,
  ...
)

# S3 method for StdAssay
ProjectCellEmbeddings(
  query,
  reference,
  reference.assay = NULL,
  reduction = "pca",
  dims = 1:50,
  scale = TRUE,
  normalization.method = NULL,
  verbose = TRUE,
  nCount_UMI = NULL,
  feature.mean = NULL,
  feature.sd = NULL,
  ...
)

# S3 method for default
ProjectCellEmbeddings(
  query,
  reference,
  reference.assay = NULL,
  reduction = "pca",
  dims = 1:50,
  scale = TRUE,
  normalization.method = NULL,
  verbose = TRUE,
  features = NULL,
  nCount_UMI = NULL,
  feature.mean = NULL,
  feature.sd = NULL,
  ...
)

# S3 method for IterableMatrix
ProjectCellEmbeddings(
  query,
  reference,
  reference.assay = NULL,
  reduction = "pca",
  dims = 1:50,
  scale = TRUE,
  normalization.method = NULL,
  verbose = TRUE,
  features = features,
  nCount_UMI = NULL,
  feature.mean = NULL,
  feature.sd = NULL,
  block.size = 10000,
  ...
)

Arguments

query: An object for query cells
reference: An object for reference cells
query.assay: Assay name for query object
reference.assay: Assay name for reference object
reduction: Name of dimensional reduction from reference object
dims: Dimensions used for reference dimensional reduction
scale: Determine if scale query data based on reference data variance
verbose: Print progress
feature.mean: Mean of features in reference
feature.sd: Standard variance of features in reference

Value

A matrix with projected cell embeddings