MPXAssay Methods

Methods for MPXAssay objects for generics defined in other packages

Usage

# S3 method for class 'MPXAssay'
RenameCells(object, new.names = NULL, ...)

# S4 method for class 'MPXAssay'
show(object)

# S3 method for class 'MPXAssay'
subset(x, features = NULL, cells = NULL, ...)

# S3 method for class 'MPXAssay'
merge(
  x = NULL,
  y = NULL,
  merge.data = TRUE,
  add.cell.ids = NULL,
  collapse = TRUE,
  ...
)

Arguments

object

A CellGraphAssay or a CellGraphAssay5 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.

...

Arguments passed to other methods

x

A MPXAssay object

features

Feature names

cells

Cell names

y

A MPXAssay object or a list of MPXAssay objects

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

Value

A MPXAssay object

Functions

• RenameCells(MPXAssay): Rename cell IDs of a CellGraphAssay or CellGraphAssay5 object

• show(MPXAssay): Show method for a CellGraphAssay or a CellGraphAssay5 object

• subset(MPXAssay): Subset a CellGraphAssay or a CellGraphAssay5 object

• merge(MPXAssay): Merge two or more CellGraphAssay or CellGraphAssay5 objects together

Examples

library(pixelatorR)
library(dplyr)
library(tidygraph)

pxl_file <- system.file("extdata/five_cells",
  "five_cells.pxl",
  package = "pixelatorR"
)
counts <- ReadMPX_counts(pxl_file)
#> ℹ Loading count data from /private/var/folders/gw/bdcqhnvs0m9gs_mq8n51jtbc0000gn/T/Rtmpn9YTAb/temp_libpath1398336799173/pixelatorR/extdata/five_cells/five_cells.pxl
edgelist <- ReadMPX_item(pxl_file, items = "edgelist")
#> ℹ Loading item(s) from: /private/var/folders/gw/bdcqhnvs0m9gs_mq8n51jtbc0000gn/T/Rtmpn9YTAb/temp_libpath1398336799173/pixelatorR/extdata/five_cells/five_cells.pxl
#> →   Loading edgelist data
#> ✔ Returning a 'tbl_df' object
components <- colnames(counts)
edgelist_split <-
  edgelist %>%
  select(upia, upib, component) %>%
  distinct() %>%
  group_by(component) %>%
  group_split() %>%
  setNames(nm = components)

# Convert data into a list of CellGraph objects
bipartite_graphs <- lapply(edgelist_split, function(x) {
  x <- x %>% as_tbl_graph(directed = FALSE)
  x <- x %>% mutate(node_type = case_when(name %in% edgelist$upia ~ "A", TRUE ~ "B"))
  attr(x, "type") <- "bipartite"
  CreateCellGraphObject(cellgraph = x)
})

# Create CellGraphAssay
cg_assay <- CreateCellGraphAssay(counts = counts, cellgraphs = bipartite_graphs)
cg_assay
#> CellGraphAssay data with 80 features for 5 cells
#> First 10 features:
#>  CD274, CD44, CD25, CD279, CD41, HLA-ABC, CD54, CD26, CD27, CD38 
#> Loaded CellGraph objects:
#>  5

# Show method
cg_assay
#> CellGraphAssay data with 80 features for 5 cells
#> First 10 features:
#>  CD274, CD44, CD25, CD279, CD41, HLA-ABC, CD54, CD26, CD27, CD38 
#> Loaded CellGraph objects:
#>  5

library(pixelatorR)
library(dplyr)
options(Seurat.object.assay.version = "v3")

pxl_file <- system.file("extdata/five_cells",
  "five_cells.pxl",
  package = "pixelatorR"
)
seur <- ReadMPX_Seurat(pxl_file)
#> ✔ Created a 'Seurat' object with 5 cells and 80 targeted surface proteins
seur <- LoadCellGraphs(seur)
#> →    Loading CellGraphs for 5 cells from sample 1
#> ✔ Successfully loaded 5 CellGraph object(s).
cg_assay <- seur[["mpxCells"]]

# Subset CellGraphAssay(5)
# ---------------------------------
cg_assay_subset <- subset(cg_assay, cells = colnames(cg_assay)[1:3])

# Subset Seurat object containing a CellGraphAssay(5)
# --------------------------------
seur_subset <- subset(seur, cells = colnames(seur)[1:3])

# Merge multiple CellGraphAssay(5) objects
# ---------------------------------

# Merge 3 CellGraphAssay(5) objects
cg_assay_merged <- merge(cg_assay,
  y = list(cg_assay, cg_assay),
  add.cell.ids = c("A", "B", "C")
)