jruffle/ae_samples_64d

Autoencoder (Sample-centric, 64D)

Pre-trained Autoencoder model for transcriptomics data compression, part of the TRACERx Datathon 2025 project.

Model Details

• Method: Autoencoder
• Compression Mode: Sample-centric
• Output Dimensions: 64
• Training Data: TRACERx open dataset (VST-normalized counts)

Usage

This model is designed to be used with the TRACERx Datathon 2025 analysis pipeline. It will be automatically downloaded and cached when needed.

import joblib

# Load the model bundle
model_data = joblib.load("model.joblib")

# Access components based on model type
# See documentation for specific usage

Files

• model.joblib: Model bundle containing fitted model and preprocessing parameters