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README.md

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+---
+title: t-SNE (t-Distributed Stochastic Neighbor Embedding) (Transcriptome-centric, 3D)
+emoji: 🧬
+colorFrom: purple
+colorTo: blue
+sdk: python
+tags:
+- transcriptomics
+- dimensionality-reduction
+- tsne
+license: mit
+---
+
+# t-SNE (t-Distributed Stochastic Neighbor Embedding) (Transcriptome-centric, 3D)
+
+Pre-trained t-SNE (t-Distributed Stochastic Neighbor Embedding) model for transcriptomics data compression, part of the TRACERx Datathon 2025 project.
+
+## Model Details
+
+- **Method**: t-SNE (t-Distributed Stochastic Neighbor Embedding)
+- **Compression Mode**: Transcriptome-centric
+- **Output Dimensions**: 3
+- **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.
+
+```python
+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