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---
tags:
- transcriptomics
- dimensionality-reduction
- classical
- TRACERx
- UMAP
- PCA
license: mit
---
# Classical Models (PCA + UMAP) - transcriptome mode - 64D
Pre-trained PCA and UMAP models for transcriptomic data compression.
**UMAP models support transform()** - new data can be projected into the same embedding space.
## Details
- **Mode**: transcriptome-centric compression
- **Dimensions**: 64
- **Training data**: TRACERx lung cancer transcriptomics
- **Created**: 2026-01-13T17:03:21.452424
- **UMAP transform**: Enabled (low_memory=False)
## Usage
```python
import joblib
from huggingface_hub import snapshot_download
# Download model
local_dir = snapshot_download("jruffle/classical_transcriptome_64d")
model = joblib.load(f"{local_dir}/model.joblib")
# Model contains: 'pca', 'umap', 'robust_scaler', 'gene_order'
# Use UMAP transform on new data:
new_embeddings = model['umap'].transform(preprocessed_new_data)
```
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