Run GPT on single-cell data — run

Ask chatGPT to summarise each cluster based on the samples metadata.

run_gpt(
  obj = NULL,
  reduction = "UMAP",
  label_var = "label",
  cluster_var = "seurat_clusters",
  terms_per_cluster = 3,
  force_new = FALSE,
  return_all_results = FALSE,
  verbose = TRUE
)

Arguments

obj: Single-cell data object.
reduction: Name of the reduction to use (case insensitive).
label_var: Which cell metadata column to input to NLP analysis.
cluster_var: Which cell metadata column to use to identify which cluster each cell is assigned to.
terms_per_cluster: The maximum number of words to return per cluster.
force_new: If NLP results are already detected the metadata, set force_new=TRUE to replace them with new results.
return_all_results: Whether to return just the obj with updated metadata (TRUE), or all intermediate results (FALSE).
verbose: Whether to print messages.

Value

The input object with GPT summary added to metadata, or if return_all_results=TRUE, a list with the object and intermediate results.

Examples

# Show expected input (API call not executed)
data("pseudo_seurat")
print(class(pseudo_seurat))
#> [1] "Seurat"
#> attr(,"package")
#> [1] "SeuratObject"