Taykhoom/functional-multiclass-gamba

GAMBA Functional Region Multiclass

This representation benchmark asks whether frozen sequence embeddings separate genomic functional categories. Each row is one annotated region; label == category.

Loading

from datasets import load_dataset

full_bidi = load_dataset(
    "Taykhoom/functional-multiclass-gamba",
    "full-bidi",
    split="all",
)

paper_test = full_bidi.filter(
    lambda row: row["split"] == "test"
    and row["category"] != "noncoding_regions"
)

Choosing a configuration

The two dimensions are independent:

Dimension	Options	Meaning
Context	causal, bidi	End-anchor ROI for autoregressive models or center it for bidirectional models.
Pooling	full, 100bp	Pool over the retained ROI or a deterministic 100 bp subspan.

The full name refers to the retained ROI visible in the 2,048 bp context; very long features may be clipped according to GAMBA's context rules. It does not mean an unlimited genomic interval.

The 100 bp span is selected deterministically from the ROI. Published pair_id values remain stable for unchanged source examples, so unrelated RepeatMasker corrections do not shift their chosen windows.

Dataset size

Config family	Complete rows	Held-out test	Corrected paper rows	Corrected paper test
full-*	94,284	18,916	84,841	16,992
100bp-*	67,626	13,593	58,646	11,781

The corrected paper view excludes category == "noncoding_regions".

Labels

Full configs contain eleven labels:

Category	Rows
repeats	9,991
UCNE	4,169
vista_enhancer	2,628
promoters	9,971
UTR5	9,802
UTR3	9,693
coding_regions	9,893
exons	9,915
introns	9,026
upstream_TSS	9,753
noncoding_regions	9,443

The 100 bp configs contain 67,626 rows. Promoter entries do not satisfy the 100 bp retained-span criterion and are absent; vista_enhancer has 2,621 rows, and other categories are filtered by eligible ROI length.

Evaluation protocol

For the corrected paper evaluation:

1. filter split == "test";
2. exclude noncoding_regions;
3. pool embeddings over the stored span;
4. perform cosine leave-one-out 1-nearest-neighbor classification;
5. report balanced accuracy.

No supervised model-fitting split is implied by Hugging Face split all.

Columns

Column group	Description
split, sequence, label, pair_id	Chromosome partition, exact input, functional class, and stable feature ID.
category, repeat_class, scope, context_policy	Source class, nullable repeat class, full/100bp scope, and context geometry.
chrom, start, end, source_strand	Zero-based, half-open hg38 coordinates and biological strand (. means unknown).
sequence_orientation	Explicit +/- orientation used for sequence geometry and reverse complementation.
context_start, context_end	Forward-genome context coordinates.
roi_start, roi_end	Retained feature offsets in oriented sequence.
pool_start_in_window, pool_end_in_window	Evaluation span; ROI or selected 100 bp subspan.
name	Source annotation identifier.
phylop_*, phylop_context_*	Pooling-span and symmetric-context phyloP summaries.

RepeatMasker correction

RepeatMasker genomic strand and repeat class are stored separately. This release corrects an earlier local conversion that placed the repeat class in the strand column, then regenerates repeat-derived contexts, pools, controls, and phyloP features. Labels are unchanged.

Processing and citation

Processing and verification:

https://github.com/TaykhoomDalal/Gamba-Processing/commit/549985683a1c52014a64c5781937dd25360f1553

Consens, M. E. et al. Predicting evolutionary rate as a pretraining task improves genome language model representations. bioRxiv (2026). https://doi.org/10.64898/2026.02.02.703275

License

The processing code derived from GAMBA is MIT licensed under the processing repository's LICENSE. This generated dataset is marked other: incorporated reference sequence, annotations, and phyloP-derived values retain their upstream terms, so no blanket MIT license is asserted for the Parquets.