Cortexa research tool·genomics·cellxgene_census

CELLxGENE Get Gene Metadata

Query gene (variable) metadata from CELLxGENE Census. Returns gene symbols, Ensembl IDs, feature types, and summary statistics. Filter by gene name, feature type, or expression characteristics. Use for: finding genes of interest, validating gene symbols, exploring feature presence across datasets.

Livelast probed 2026-05-01 01:00Z· 648msCortexa

Status

The most recent probe succeeded. Safe to call from the agent today.

Last probed: 1d ago
Last success: 1d ago
Last latency: 648ms

Schema

JSON Schema the agent (or your API call) must match.

{
  "properties": {
    "census_version": {
      "default": "stable",
      "description": "Census version to query. 'stable' (recommended, Long-Term Support release), 'latest' (newest data, may change), or specific date 'YYYY-MM-DD' (for reproducibility). Default 'stable' is best for production analyses.",
      "type": "string"
    },
    "column_names": {
      "description": "Specific columns to return (default: all columns)",
      "items": {
        "type": "string"
      },
      "type": "array"
    },
    "operation": {
      "default": "get_var_metadata",
      "description": "Operation type",
      "enum": [
        "get_var_metadata"
      ],
      "type": "string"
    },
    "organism": {
      "default": "Homo sapiens",
      "description": "Organism name",
      "enum": [
        "Homo sapiens",
        "Mus musculus"
      ],
      "type": "string"
    },
    "var_value_filter": {
      "description": "Filter genes using SQL-like syntax. Format: 'field == \"value\"'. Common fields: feature_name (gene symbol), feature_id (Ensembl ID), feature_biotype. Examples: 'feature_name == \"TP53\"', 'feature_name in [\"CD4\", \"CD8A\"]', 'feature_biotype == \"protein_coding\"'.",
      "type": "string"
    }
  },
  "required": [
    "operation"
  ],
  "type": "object"
}

Examples (1)

Default CELLxGENE Get Gene Metadata call

public-safeinput

{
  "column_names": [],
  "operation": ""
}

Expected response keys: success

Anonymous-safe example. Rate-limited; no sign-in required.

Identifiers

Catalog ID: tu_CELLxGENE_get_gene_metadata
Tool name: CELLxGENE_get_gene_metadata
Added: 2026-05-01 00:58Z
Tags: tooluniverse

CELLxGENE Get Gene Metadata

Livelast probed 2026-05-01 01:00Z· 648msCortexa

Schema

JSON Schema the agent (or your API call) must match.

{ "properties": { "census_version": { "default": "stable", "description": "Census version to query. 'stable' (recommended, Long-Term Support release), 'latest' (newest data, may change), or specific date 'YYYY-MM-DD' (for reproducibility). Default 'stable' is best for production analyses.", "type": "string" }, "column_names": { "description": "Specific columns to return (default: all columns)", "items": { "type": "string" }, "type": "array" }, "operation": { "default": "get_var_metadata", "description": "Operation type", "enum": [ "get_var_metadata" ], "type": "string" }, "organism": { "default": "Homo sapiens", "description": "Organism name", "enum": [ "Homo sapiens", "Mus musculus" ], "type": "string" }, "var_value_filter": { "description": "Filter genes using SQL-like syntax. Format: 'field == \"value\"'. Common fields: feature_name (gene symbol), feature_id (Ensembl ID), feature_biotype. Examples: 'feature_name == \"TP53\"', 'feature_name in [\"CD4\", \"CD8A\"]', 'feature_biotype == \"protein_coding\"'.", "type": "string" } }, "required": [ "operation" ], "type": "object" }