metadata
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
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)