---
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)
```