Create reasoning-aware prompt for cell type annotation

This prompt is built from its own template rather than derived from create_annotation_prompt(), so the two prompts can evolve independently. The template mirrors REASONING_PROMPT_TEMPLATE in the Python package (python/mllmcelltype/prompts.py) so both implementations ask for the same structured JSON output; it is adapted to the R signature, which takes a single tissue_name instead of separate species/tissue arguments.

Usage

create_reasoning_annotation_prompt(input, tissue_name, top_gene_count = 10)

Arguments

input

Either a data frame from Seurat's FindAllMarkers() or a list for each cluster where each element is either a character vector of genes or a list containing a genes field.

tissue_name

Tissue context for the annotation (e.g., 'human PBMC', 'mouse brain')

top_gene_count

Number of top genes to use per cluster when input is from Seurat. Default: 10

Value

A list with prompt (formatted prompt text), expected_count (number of clusters), and gene_lists (cluster ID to marker genes mapping).