| # Paired Refinement Experiments |
|
|
| This directory evaluates masked diffusion as an enhancer refiner rather than as a pure de novo generator. |
|
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| For each reference sequence `x`, the script creates edited variants `x'` under a mutation budget `rho`, scores both sequences with the trained DeepSTARR predictor, and reports: |
|
|
| ```text |
| delta = predictor(x') - predictor(x) |
| ``` |
|
|
| ## Experiments covered |
|
|
| 1. Paired delta distribution over `rho = 0.01, 0.03, 0.05, 0.10, 0.20`. |
| 2. Mask-selection strategy comparison: |
| - `random`: randomly chosen editable positions. |
| - `entropy`: positions where the diffusion model is most uncertain. |
| - `logit_gap`: positions where the diffusion model most prefers a different base than the current base. |
| 3. Best-of-N refinement: |
| - sample multiple edits per sequence and keep the candidate with the largest predicted activity gain. |
|
|
| ## Outputs |
|
|
| The default output directory is: |
|
|
| ```text |
| ${RESULT_ROOT}/refinement/paired_refinement_test |
| ``` |
|
|
| It contains: |
|
|
| ```text |
| refinement_details.jsonl |
| refinement_summary.json |
| paired_delta_by_mask_ratio.png |
| strategy_delta_violin.png |
| best_of_n_refinement_curve.png |
| ``` |
|
|
| ## Recommended command on the GPU server |
|
|
| Run from the repository root. Use explicit environment variables to avoid stale defaults from `env.sh`. |
|
|
| ```bash |
| cd /inspire/hdd/project/intelligentcreativedesign/dangshengqi-253114050252/z-anna/genrl-enhancer-diffusion |
| |
| PROJECT_ROOT=$(pwd) \ |
| RUN_ROOT=$(pwd)/paper_runs \ |
| DEEPSTARR_DIR=$(pwd)/datas/DeepSTARR-enhancer-activity \ |
| GENERANNO_BASE_MODEL=$(pwd)/models/GENERanno-eukaryote-0.5b-base \ |
| DIFFUSION_MODEL=$(pwd)/saved_model/deepstarr_discrete_diffusion \ |
| PREDICTOR_MODEL=$(pwd)/paper_runs/results/deepstarr_regression/best_model \ |
| REFINEMENT_SPLIT=test \ |
| REFINEMENT_NUM_SEQUENCES=1024 \ |
| REFINEMENT_NUM_SAMPLES=8 \ |
| REFINEMENT_MASK_RATIOS="0.01 0.03 0.05 0.10 0.20" \ |
| REFINEMENT_STRATEGIES="random entropy logit_gap" \ |
| REFINEMENT_DIFFUSION_STEPS=32 \ |
| REFINEMENT_BATCH_SIZE=16 \ |
| PREDICTOR_SCORE_BATCH_SIZE=256 \ |
| TRANSFORMERS_NO_TF=1 \ |
| USE_TF=0 \ |
| TOKENIZERS_PARALLELISM=false \ |
| nohup bash scripts/11_refinement/run_paired_refinement.sh > paired_refinement.log 2>&1 & |
| ``` |
|
|
| For a fast smoke test: |
|
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| ```bash |
| PROJECT_ROOT=$(pwd) \ |
| RUN_ROOT=$(pwd)/paper_runs \ |
| DEEPSTARR_DIR=$(pwd)/datas/DeepSTARR-enhancer-activity \ |
| GENERANNO_BASE_MODEL=$(pwd)/models/GENERanno-eukaryote-0.5b-base \ |
| DIFFUSION_MODEL=$(pwd)/saved_model/deepstarr_discrete_diffusion \ |
| PREDICTOR_MODEL=$(pwd)/paper_runs/results/deepstarr_regression/best_model \ |
| REFINEMENT_SPLIT=valid \ |
| REFINEMENT_NUM_SEQUENCES=64 \ |
| REFINEMENT_NUM_SAMPLES=2 \ |
| REFINEMENT_MASK_RATIOS="0.03 0.10" \ |
| REFINEMENT_STRATEGIES="random logit_gap" \ |
| REFINEMENT_DIFFUSION_STEPS=16 \ |
| REFINEMENT_BATCH_SIZE=16 \ |
| PREDICTOR_SCORE_BATCH_SIZE=128 \ |
| TRANSFORMERS_NO_TF=1 \ |
| USE_TF=0 \ |
| TOKENIZERS_PARALLELISM=false \ |
| nohup bash scripts/11_refinement/run_paired_refinement.sh > paired_refinement_smoke.log 2>&1 & |
| ``` |
|
|
