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
TableJSON 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. |