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bioinfoihb/Fish_GUE

FishGUE FishGUE is a unified fish genomics benchmark developed for evaluating DNA foundation models and other sequence models on fish genomic prediction tasks. It was introduced in the FishNALM study, where it was used to systematically benchmark fish-specific and general DNA language models across diverse regulatory sequence prediction tasks. Dataset summary FishGUE contains 17 supervised prediction tasks spanning four task groups: Histone mark prediction… See the full description on the dataset page: https://huggingface.co/datasets/bioinfoihb/Fish_GUE.

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FishGUE

FishGUE is a unified fish genomics benchmark developed for evaluating DNA foundation models and other sequence models on fish genomic prediction tasks.

It was introduced in the FishNALM study, where it was used to systematically benchmark fish-specific and general DNA language models across diverse regulatory sequence prediction tasks.

Dataset summary

FishGUE contains 17 supervised prediction tasks spanning four task groups:

  • Histone mark prediction
  • Transcription factor binding-site prediction
  • Promoter prediction
  • Splice-site prediction

The benchmark covers input sequence lengths from 300 bp to 2500 bp and includes both zebrafish-based datasets and multi-species cyprinid splice datasets.

Why FishGUE?

Fish genomic benchmarks remain limited compared with those available for human, plant, or broad multi-species genomic modeling. FishGUE was constructed to provide a unified benchmark for evaluating model performance on representative fish genomic sequence prediction problems, especially those relevant to regulatory sequence recognition and gene structure annotation.

Benchmark composition

The FishGUE benchmark includes the following 17 tasks.

CategoryTaskSpeciesSequence length (bp)Train / Val / Test
Histone mark predictionH3K4me1Danio reriovariable (≤2500)48815 / 6102 / 6102
Histone mark predictionH3K4me3Danio reriovariable (≤2500)47482 / 5935 / 5936
Histone mark predictionH3K9me3Danio reriovariable (≤2500)40125 / 5016 / 5016
Histone mark predictionH3K27acDanio reriovariable (≤2500)27611 / 3451 / 3452
Histone mark predictionH3K27me3Danio reriovariable (≤2500)27017 / 3377 / 3378
TF binding-site predictionCTCFDanio rerio80028526 / 3566 / 3566
TF binding-site predictionPou5f1Danio rerio80011128 / 1391 / 1391
TF binding-site predictionSox2Danio rerio8009717 / 1215 / 1215
Promoter predictionCore promoterDanio rerio30017222 / 2153 / 2153
Promoter predictionCore promoter (TATA)Danio rerio3003464 / 433 / 434
Promoter predictionCore promoter (non-TATA)Danio rerio30013757 / 1720 / 1720
Promoter predictionPromoterDanio rerio100017222 / 2153 / 2153
Promoter predictionPromoter (TATA)Danio rerio10003464 / 433 / 434
Promoter predictionPromoter (non-TATA)Danio rerio100013757 / 1720 / 1720
Splice-site predictionSplicing (acceptor)Cyprinidae (5 species)60017200 / 2150 / 2150
Splice-site predictionSplicing (donor)Cyprinidae (5 species)60027600 / 3450 / 3450
Splice-site predictionSplicing (both)Cyprinidae (5 species)6001720 / 2150 / 2105

Data sources and construction overview

According to the FishNALM manuscript, FishGUE was assembled from the following sources:

  • Histone mark datasets were derived from public zebrafish ChIP-seq peak datasets.
  • Transcription factor binding-site datasets were built from public ChIP-seq peaks for CTCF, Pou5f1, and Sox2.
  • Promoter datasets were constructed from zebrafish promoter annotations from the Eukaryotic Promoter Database (EPD).
  • Splice-site datasets were compiled from annotated genomes of five cyprinid fish species.

For all tasks, positive and negative examples were constructed through task-specific processing, then split into training, validation, and test sets using an 8:1:1 ratio.

Suggested repository organization

If you plan to upload FishGUE as a single Hugging Face dataset repository, a clean structure is:

text
FishGUE/
├── README.md
├── histone/
│   ├── H3K4me1_train.tsv
│   ├── H3K4me1_val.tsv
│   ├── H3K4me1_test.tsv
│   └── ...
├── tfbs/
│   ├── CTCF_train.tsv
│   ├── CTCF_val.tsv
│   ├── CTCF_test.tsv
│   └── ...
├── promoter/
│   ├── core_promoter_300_train.tsv
│   └── ...
└── splice/
    ├── splice_acceptor_train.tsv
    └── ...

If your files are already packaged in another layout, you can keep that layout and simply explain it in this README.

Intended uses

FishGUE is intended for:

  • benchmarking DNA foundation models on fish genomic sequence prediction tasks
  • evaluating transfer learning performance in fish genomics
  • comparing task robustness across promoter, chromatin, TFBS, and splice-site prediction settings
  • developing new fish-specific sequence models and downstream classifiers

Limitations

  • Most non-splice tasks are based on zebrafish data.
  • The splice-site benchmark uses five cyprinid species, so broader phylogenetic coverage remains limited.
  • FishGUE is designed as a research benchmark and should not be interpreted as a clinical or diagnostic dataset.
  • Performance on FishGUE does not guarantee performance on all fish species or all regulatory genomics tasks.

Citation

If you use FishGUE in your work, please cite the FishNALM manuscript.

Manuscript:

FishNALM: A Foundation DNA Language Model for Fish Genomes

Project links

Contact

Xiao-Qin Xia Institute of Hydrobiology, Chinese Academy of Sciences Email: xqxia@ihb.ac.cn Email: bioinfoihb@ihb.ac.cn