diffmap

diffmap

Reduce data dimensionality using Diffusion Maps on the SCMCP server. Specify components, neighbors, and random states for precise, reproducible single-cell RNA sequencing analysis.

Instructions

Diffusion Maps for dimensionality reduction

Input Schema

Name	Required	Description
`n_comps`	No	The number of dimensions of the representation.
`neighbors_key`	No	If not specified, diffmap looks .uns['neighbors'] for neighbors settings and .obsp['connectivities'], .obsp['distances'] for connectivities and distances respectively. If specified, diffmap looks .uns[neighbors_key] for neighbors settings and uses the corresponding connectivities and distances.
`random_state`	No	Random seed for reproducibility.

Input Schema (JSON Schema)

{
  "description": "Input schema for the Diffusion Maps dimensionality reduction tool.",
  "properties": {
    "n_comps": {
      "default": 15,
      "description": "The number of dimensions of the representation.",
      "exclusiveMinimum": 0,
      "title": "N Comps",
      "type": "integer"
    },
    "neighbors_key": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "If not specified, diffmap looks .uns['neighbors'] for neighbors settings and .obsp['connectivities'], .obsp['distances'] for connectivities and distances respectively. If specified, diffmap looks .uns[neighbors_key] for neighbors settings and uses the corresponding connectivities and distances.",
      "title": "Neighbors Key"
    },
    "random_state": {
      "default": 0,
      "description": "Random seed for reproducibility.",
      "title": "Random State",
      "type": "integer"
    }
  },
  "title": "DiffMapModel",
  "type": "object"
}

SCMCP

Instructions

Input Schema

Input Schema (JSON Schema)

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MCP directory API