Create a CellGraph object

Usage

CreateCellGraphObject(
  cellgraph,
  counts = NULL,
  layout = NULL,
  layers = NULL,
  meta.data = NULL,
  reductions = NULL,
  verbose = FALSE
)

Arguments

cellgraph: A tbl_graph object representing a PNA single-cell graph
counts: A dgCMatrix with marker counts. Rows are matched to graph node names (order does not need to match).
layout: A named list of data.frame objects with cell layouts. Nodes are identified by row names or by a name column; otherwise the row order is assumed to follow the graph. MPX bipartite layouts may use unsuffixed names while graph nodes keep -A/-B; those names are matched after stripping the suffix, as in LoadCellGraphs. Stored layouts keep graph node order and do not copy node IDs as row names.
layers: A named list of additional numeric node matrices (nodes x features). "counts" is reserved.
meta.data: A node-level data.frame or tbl_df. Either row names or a name column must identify nodes.
reductions: A named list of NodeDimReduc objects
verbose: Print messages

Value

A CellGraph object

Details

Node-level variable names must not clash between the graph node table, meta.data, reduction embeddings, and matrix features. Count and layer matrices may share feature names because methods such as FetchData select a specific layer.

Examples


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

# Open a database connection (PXL file)
db <- PixelDB$new(minimal_pna_pxl_file())
#> duckdb keeps downloaded extensions and secrets in a temporary directory:
#> ℹ /tmp/RtmpjKKHFf/duckdb
#> This is removed when the R session ends.
#> • Extensions are re-downloaded each session.
#> • Secrets are lost.
#> ℹ Run duckdb(shared_home = TRUE) (or create ~/.duckdb) to keep them (suitable for most users).
#> ℹ Run duckdb(shared_home = FALSE) to accept the temporary directory (and silence this message).
#> ℹ See ?duckdb_storage for details and alternatives.

# Select a component ID and load the edgelist
sel_comp <- db$cell_meta() %>%
  rownames() %>%
  head(1)
component_edgelist <- db$components_edgelist(
  components = sel_comp,
  umi_data_type = "suffixed_string"
) %>%
  select(umi1, umi2)

# Define node types for the bipartite graph
umi_node_type <- bind_rows(
  component_edgelist %>% select(name = umi1) %>% mutate(node_type = "umi1"),
  component_edgelist %>% select(name = umi2) %>% mutate(node_type = "umi2")
) %>%
  distinct()

# Create a bipartite graph from the edgelist and add node types
component_graph <- as_tbl_graph(component_edgelist, directed = FALSE) %N>%
  left_join(umi_node_type, by = "name")

# Set the graph type attribute to "bipartite"
attr(component_graph, "type") <- "bipartite"

# Create a CellGraph object with just the graph
cg <- CreateCellGraphObject(cellgraph = component_graph)
cg
#> A CellGraph object containing a bipartite graph with 43543 nodes and 97014 edges

# Load cell count matrix
counts <- db$components_marker_counts(
  components = sel_comp, as_sparse = TRUE
)[[1]]

# Create a CellGraph object with graph and counts
cg <- CreateCellGraphObject(cellgraph = component_graph, counts = counts)
cg
#> A CellGraph object containing a bipartite graph with 43543 nodes and 97014 edges
#> Number of markers:  149 

# Create a CellGraph object with counts and layout
layout <- db$components_layout(
  components = sel_comp
)[[1]]
#> ℹ Fetching 1 component layouts...

# Layouts with a name column or node row names are matched automatically
cg <- CreateCellGraphObject(
  cellgraph = component_graph,
  counts = counts,
  layout = list(wpmds_3d = layout)
)
cg
#> A CellGraph object containing a bipartite graph with 43543 nodes and 97014 edges
#> Number of markers:  149 
#> Layouts: wpmds_3d