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"
}