ProjectCellEmbeddings {Seurat} | R Documentation |
Project query data to the reference dimensional reduction
Description
Project query data to the reference dimensional reduction
Usage
ProjectCellEmbeddings(query, ...)
## S3 method for class '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 class '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 class '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 class '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,
...
)
## Default S3 method:
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 class '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
[Package Seurat version 5.1.0 Index]