Publish reviewed GAMBA evaluation dataset

README.md

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+---
+pretty_name: "GAMBA Functional Region Multiclass"
+license: mit
+tags:
+- biology
+- genomics
+- dna
+- genome-language-model
+- benchmark
+- functional-genomics
+- multiclass-classification
+- hg38
+- parquet
+configs:
+- config_name: full
+  data_files:
+  - split: all
+    path: functional-multiclass-gamba-full.parquet
+- config_name: 100bp
+  data_files:
+  - split: all
+    path: functional-multiclass-gamba-100bp.parquet
+- config_name: full-noncoding-added
+  data_files:
+  - split: all
+    path: functional-multiclass-gamba-full-noncoding-added.parquet
+- config_name: 100bp-noncoding-added
+  data_files:
+  - split: all
+    path: functional-multiclass-gamba-100bp-noncoding-added.parquet
+---
+
+# GAMBA Functional Region Multiclass
+
+This dataset packages GAMBA's multiclass functional-region benchmark. Each row
+is an annotated feature labeled by its functional category.
+
+The full-region and 100 bp pooling variants are separate Hugging Face configs.
+Both retain the same GAMBA-oriented context sequence; `pool_start` and
+`pool_end` select either the complete ROI or a deterministic 100 bp subspan.
+ROIs shorter than 100 bp are absent from the 100 bp configs.
+
+GAMBA's evaluator selects the 100 bp subspan using Python's process-randomized
+`hash()`. This release uses BLAKE2 over the same seed, category, and pair ID so
+the saved subset is stable across machines.
+
+## Configs
+
+| Config | Train rows | Test rows | Total | Pooling span |
+|---|---:|---:|---:|---|
+| `full` | 67,846 | 16,991 | 84,837 | complete ROI |
+| `100bp` | 46,862 | 11,781 | 58,643 | 100 bp |
+| `full-noncoding-added` | 75,363 | 18,917 | 94,280 | complete ROI |
+| `100bp-noncoding-added` | 54,028 | 13,595 | 67,623 | 100 bp |
+
+The two `noncoding-added` configs are explicit extensions from
+[Gamba-Processing](https://github.com/TaykhoomDalal/Gamba-Processing), not an
+additional category emitted by GAMBA's current `create_eval_data.py`.
+
+## Loading
+
+```python
+from datasets import load_dataset
+
+full = load_dataset(
+    "Taykhoom/functional-multiclass-gamba",
+    "full",
+    split="all",
+)
+train = full.filter(lambda row: row["split"] == "train")
+test = full.filter(lambda row: row["split"] == "test")
+```
+
+## Columns
+
+| Column | Description |
+|---|---|
+| `split`, `label` | Probe/fine-tuning `train` or held-out `test`; `label` is the functional category. |
+| `sequence` | Strand-oriented GAMBA context of at most 2,048 bp. |
+| `pair_id` | Stable GAMBA feature/control identifier. |
+| `category`, `scope` | Functional category and `full` or `100bp`. |
+| `chrom`, `start`, `end`, `strand` | Zero-based, half-open hg38 feature coordinates. |
+| `context_start`, `context_end` | Forward-genome coordinates of `sequence`. |
+| `roi_start`, `roi_end` | Full feature offsets within `sequence`. |
+| `pool_start`, `pool_end` | Full-ROI or fixed 100 bp pooling span. |
+| `name` | Source annotation name. |
+
+## Data source and processing
+
+The processing code reproduces the ten-category BED output from
+[Microsoft GAMBA](https://github.com/microsoft/gamba) commit `e83984e`
+byte-for-byte, then freezes all GAMBA autosomes plus `chrX` in parquet.
+The GAMBA models were pretrained on the chromosomes marked `train`. The paper's
+zero-shot result used the frozen models on `chr2`, `chr3`, `chr16`, and
+`chr22`, which are marked `test`; no task-specific model was fitted on these
+benchmark rows. Use only `test` to reproduce that paper subset. The `train`
+rows are provided for probing/fine-tuning or broader chromosome evaluation.
+
+## Citation
+
+Please cite the GAMBA paper:
+
+Consens, M. E. et al. *Predicting evolutionary rate as a pretraining task
+improves genome language model representations*. bioRxiv (2026).
+[doi:10.64898/2026.02.02.703275](https://doi.org/10.64898/2026.02.02.703275).
+A conference version is available on
+[OpenReview](https://openreview.net/forum?id=dkgM2ale4U).
+
+```bibtex
+@article{consens2026predicting,
+  title = {Predicting evolutionary rate as a pretraining task improves genome language model representations},
+  author = {Consens, Micaela Elisa and Yang, Kevin K. and Hall, Jimmy and Conard, Ashley Mae and Wang, Bo and Crawford, Lorin and Moses, Alan and Lu, Alex X.},
+  journal = {bioRxiv},
+  year = {2026},
+  doi = {10.64898/2026.02.02.703275},
+  url = {https://doi.org/10.64898/2026.02.02.703275}
+}
+```
+
+## License
+
+GAMBA and its released benchmark code/data are distributed under the MIT
+license. Upstream annotation resources retain their original terms.

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