tsne

tsne

Visualize high-dimensional single-cell data with t-distributed stochastic neighborhood embedding (t-SNE) to uncover patterns and clusters in an intuitive 2D or 3D space.

Instructions

t-distributed stochastic neighborhood embedding (t-SNE), for visualizating single-cell data

Input Schema

Name	Required	Description	Default
`early_exaggeration`	No	Controls space between natural clusters in embedded space.
`learning_rate`	No	Learning rate for optimization, typically between 100-1000.
`metric`	No	Distance metric to use.	euclidean
`n_jobs`	No	Number of jobs for parallel computation.
`n_pcs`	No	Number of PCs to use. If None, automatically determined.
`perplexity`	No	Related to number of nearest neighbors, typically between 5-50.
`random_state`	No	Random seed for reproducibility.
`use_fast_tsne`	No	Whether to use Multicore-tSNE implementation.
`use_rep`	No	Key for .obsm to use as representation.

Input Schema (JSON Schema)

{
  "description": "Input schema for the t-SNE dimensionality reduction tool.",
  "properties": {
    "early_exaggeration": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "integer"
        }
      ],
      "default": 12,
      "description": "Controls space between natural clusters in embedded space.",
      "gt": 0,
      "title": "Early Exaggeration"
    },
    "learning_rate": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "integer"
        }
      ],
      "default": 1000,
      "description": "Learning rate for optimization, typically between 100-1000.",
      "gt": 0,
      "title": "Learning Rate"
    },
    "metric": {
      "default": "euclidean",
      "description": "Distance metric to use.",
      "title": "Metric",
      "type": "string"
    },
    "n_jobs": {
      "anyOf": [
        {
          "exclusiveMinimum": 0,
          "type": "integer"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Number of jobs for parallel computation.",
      "title": "N Jobs"
    },
    "n_pcs": {
      "anyOf": [
        {
          "minimum": 0,
          "type": "integer"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Number of PCs to use. If None, automatically determined.",
      "title": "N Pcs"
    },
    "perplexity": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "integer"
        }
      ],
      "default": 30,
      "description": "Related to number of nearest neighbors, typically between 5-50.",
      "gt": 0,
      "title": "Perplexity"
    },
    "random_state": {
      "default": 0,
      "description": "Random seed for reproducibility.",
      "title": "Random State",
      "type": "integer"
    },
    "use_fast_tsne": {
      "default": false,
      "description": "Whether to use Multicore-tSNE implementation.",
      "title": "Use Fast Tsne",
      "type": "boolean"
    },
    "use_rep": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Key for .obsm to use as representation.",
      "title": "Use Rep"
    }
  },
  "title": "TSNEModel",
  "type": "object"
}

SCMCP

Instructions

Input Schema

Input Schema (JSON Schema)

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