Transcriptformer Tools

Configuration File: remote_tools/transcriptformer_tools.json Tool Type: Remote Tools Count: 1

This page contains all tools defined in the transcriptformer_tools.json configuration file.

Available Tools

run_transcriptformer_embedding_retrieval (Type: RemoteTool)

Retrieves contextualized gene embeddings from Transcriptformer models. This tool provides access …

run_transcriptformer_embedding_retrieval tool specification

Tool Information:

  • Name: run_transcriptformer_embedding_retrieval

  • Type: RemoteTool

  • Description: Retrieves contextualized gene embeddings from Transcriptformer models. This tool provides access to pre-computed Transcriptformer embeddings that capture gene expression patterns learned from single-cell RNA sequencing data. The embeddings are contextualized for specific combinations of disease states and cell types, enabling precise analysis of gene behavior in relevant biological contexts.

Parameters:

  • state (string) (required) Disease state context for embedding retrieval. Examples: ‘control’: Healthy/normal condition; ‘disease’: Disease-affected state; ‘treated’: Post-treatment condition; ‘untreated’: Pre-treatment condition. Must match available states in the disease-specific store.

  • cell_type (string) (required) Cell type context for embeddings. Examples: ‘b_cell’: B lymphocytes; ‘t_cell’: T lymphocytes; ‘macrophage’: Tissue macrophages; ‘epithelial_cell’: Epithelial cells; ‘fibroblast’: Connective tissue fibroblasts. Must match available cell types in the disease store.

  • gene_names (array) (required) Gene identifiers for embedding retrieval: Gene symbols: [‘TP53’, ‘BRCA1’, ‘EGFR’, ‘MYC’]; Ensembl IDs: [‘ENSG00000141510’, ‘ENSG00000139618’]; Mixed formats supported; Empty list retrieves all available genes.

  • disease (string) (required) Disease/dataset identifier. Examples: ‘breast_cancer’: Breast cancer scRNA-seq data; ‘lung_cancer’: Lung cancer contexts; ‘diabetes’: Diabetes-related datasets; ‘alzheimer’: Alzheimer’s disease contexts. Must match available disease stores.

Example Usage:

query = {
    "name": "run_transcriptformer_embedding_retrieval",
    "arguments": {
        "state": "example_value",
        "cell_type": "example_value",
        "gene_names": ["item1", "item2"],
        "disease": "example_value"
    }
}
result = tu.run(query)