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 | Default |
|---|---|---|---|
| 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"
}