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README.md

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+---
+license: mit
+tags:
+  - synthetic-lethality
+  - gene-encoder
+  - depmap
+  - masked-autoencoder
+  - cancer-biology
+language: en
+datasets:
+  - custom
+pipeline_tag: feature-extraction
+---
+
+# SL-Predict: Frozen MAE Gene Encoder
+
+Pretrained masked-autoencoder (MAE) gene encoder for cold-start synthetic lethality prediction from DepMap CRISPR screens.
+
+## Model Description
+
+A 3-layer MLP encoder (1206 → 512 → 256 → 256) trained to reconstruct randomly masked DepMap Chronos dependency profiles (18,531 genes × 1,206 non-K562 cell lines) with MSE loss for 200 epochs.
+
+**Key property:** This is the **leak-repaired** checkpoint — the 503-gene union of all downstream cold-start test sets was excluded from pretraining. TOST equivalence testing confirms the encoder is not load-bearing on pretrain–test gene overlap (p_max < 0.0001 at ±0.010 AUC).
+
+## Performance
+
+When frozen and combined with LightGBM + confidence weighting on SynLethDB CRISPR/CRISPRi labels:
+
+| Metric | Value |
+|--------|-------|
+| Horlbeck K562 held-out AUC | **0.714 ± 0.018** (10-seed, gene-disjoint) |
+| vs Published SOTA (SLMGAE) | +0.079 |
+| vs Label-agreement ceiling | +0.015 |
+
+## Usage
+
+```python
+import torch
+
+# Load checkpoint
+ckpt = torch.load("mae_encoder_d256_leak_repaired.ckpt", map_location="cpu")
+state_dict = ckpt["state_dict"]
+
+# The encoder is the first 3 layers of the MAE
+# Input: 1206-dim DepMap dependency profile (z-scored)
+# Output: 256-dim gene embedding
+```
+
+## Training Details
+
+- **Data:** DepMap 26Q1 Chronos dependency profiles
+- **Architecture:** MLP 1206→512→256→256 (encoder), mirror decoder
+- **Objective:** Masked autoencoding (50% masking ratio, MSE loss)
+- **Epochs:** 200
+- **Hardware:** Single NVIDIA A10G (Modal cloud), ~20 minutes
+- **Leak repair:** 503 test-split genes excluded from pretraining data
+
+## Citation
+
+```
+@misc{large2026slpredict,
+  author = {Large, Jack},
+  title = {Cold-start synthetic lethality prediction: Diagnosing evaluation inflation and a constructive baseline},
+  year = {2026},
+  url = {https://github.com/j8ckfi/sl-predict}
+}
+```
+
+## Links
+
+- **Paper:** [GitHub](https://github.com/j8ckfi/sl-predict)
+- **Code:** [https://github.com/j8ckfi/sl-predict](https://github.com/j8ckfi/sl-predict)