Overview
This page focuses on expression-layer retrieval workflows after metadata filtering.
library(cellNexus)
library(dplyr)
metadata <- get_metadata(cloud_metadata = SAMPLE_DATABASE_URL)Retrieve expression by representation
Single-cell counts
sce_counts <- query_metadata |>
get_single_cell_experiment()Counts per million
sce_cpm <- query_metadata |>
get_single_cell_experiment(assays = "cpm")Pseudobulk
pb_counts <- query_metadata |>
get_pseudobulk()Targeted gene queries
# ENSEMBL IDs are expected
sce_gene <- query_metadata |>
get_single_cell_experiment(
assays = "cpm",
features = "ENSG00000134644"
)Output options
# Seurat conversion
seurat_obj <- query_metadata |>
get_seurat()
# Portable output examples
saveRDS(sce_counts, "single_cell_counts.rds")
HDF5Array::saveHDF5SummarizedExperiment(
sce_counts,
"single_cell_counts",
replace = TRUE,
as.sparse = TRUE
)
anndataR::write_h5ad(sce_counts, "single_cell_counts.h5ad")Interpretation notes
- Use
countsfor raw-scale abundance. - Use
cpmfor normalized cross-cell comparisons. - Use pseudobulk for sample/cell-type aggregation analyses.
- Use metacells for robust grouped-cell expression summarization.
sessionInfo()
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