
PNAAssay5 Methods
PNAAssay5-methods.Rd
Methods for PNAAssay5
objects for generics defined in other
packages
Join Layers Together
Usage
# S3 method for class 'PNAAssay5'
RenameCells(object, new.names = NULL, ...)
# S4 method for class 'PNAAssay5'
show(object)
# S3 method for class 'PNAAssay5'
subset(x, features = NULL, cells = NULL, ...)
# S3 method for class 'PNAAssay5'
merge(
x = NULL,
y = NULL,
merge.data = TRUE,
add.cell.ids = NULL,
collapse = TRUE,
...
)
# S3 method for class 'PNAAssay5'
JoinLayers(object, layers = NULL, new = NULL, ...)
Arguments
- object
A
PNAAssay5
object.- new.names
A character vector with new cell IDs. The length of the vector must be equal to the number of cells in the object and the names must be unique.
- ...
Additional arguments passed to other methods
- x
A
PNAAssay5
object- features
Feature names
- cells
Cell names
- y
- merge.data
Merge the data slots instead of just merging the counts (which requires renormalization); this is recommended if the same normalization approach was applied to all objects
- add.cell.ids
A character vector with sample names
- collapse
If TRUE, merge layers of the same name together
- layers
A character vector of layer names to join.
- new
Name of new layers
Functions
RenameCells(PNAAssay5)
: Rename cell IDs of aPNAAssay5
objectshow(PNAAssay5)
: Show method forPNAAssay5
objectssubset(PNAAssay5)
: Subset aPNAAssay5
objectmerge(PNAAssay5)
: Merge two or morePNAAssay5
objects togetherJoinLayers(PNAAssay5)
: Join layers
Examples
library(SeuratObject)
options(Seurat.object.assay.version = "v5")
# Load example data as a Seurat object
pxl_file <- minimal_pna_pxl_file()
seur_obj <- ReadPNA_Seurat(pxl_file)
#> ✔ Created a <Seurat> object with 5 cells and 158 targeted surface proteins
# Merge Seurat objects
seur_obj_merged <- merge(seur_obj, seur_obj)
#> Warning: Some cell names are duplicated across objects provided. Renaming to enforce unique cell names.
pna_assay <- seur_obj_merged[["PNA"]]
# The PNAAssay5 now has two count matrices
pna_assay
#> PNAAssay (v5) data with 158 features for 10 cells
#> Top 10 variable features:
#> HLA-ABC, B2M, CD11b, CD11c, CD18, CD82, CD8, TCRab, HLA-DR, CD45
#> Layers:
#> counts.1, counts.2
#> Loaded CellGraph objects:
#> 0
# Join layers
pna_assay <- JoinLayers(pna_assay)
# Now the PNAAssay5 has a single, merged count matrix
pna_assay
#> PNAAssay (v5) data with 158 features for 10 cells
#> Top 10 variable features:
#> HLA-ABC, B2M, CD11b, CD11c, CD18, CD82, CD8, TCRab, HLA-DR, CD45
#> Layers:
#> counts
#> Loaded CellGraph objects:
#> 0
# JoinLayers now also works on the Seurat object directly
seur_obj_merged <- JoinLayers(seur_obj_merged)
seur_obj_merged[["PNA"]]
#> PNAAssay (v5) data with 158 features for 10 cells
#> Top 10 variable features:
#> HLA-ABC, B2M, CD11b, CD11c, CD18, CD82, CD8, TCRab, HLA-DR, CD45
#> Layers:
#> counts
#> Loaded CellGraph objects:
#> 0