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Error code:   StreamingRowsError
Exception:    UnicodeDecodeError
Message:      'utf-8' codec can't decode byte 0x9e in position 0: invalid start byte
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 544, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3052, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 558, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/fasta/fasta.py", line 247, in _generate_tables
                  for record in self._parse_fasta(fp, include_record=include_record):
                                ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/fasta/fasta.py", line 140, in _parse_fasta
                  for line in fp:
                              ^^
                File "<frozen codecs>", line 325, in decode
              UnicodeDecodeError: 'utf-8' codec can't decode byte 0x9e in position 0: invalid start byte

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NTv3 Annotation Dataset

Genomes and reference gene annotations behind the NTv3 gene-annotation models (NTv3_annot_mammals, NTv3_annot_plants, NTv3_annot_insects). It holds two things:

  • The benchmark: the 17 test species held out from training (2 mammals, 5 plants, 10 insects). Each species comes with its complete soft-masked genome, the reference annotation the benchmark scores against, and the reference's every annotated isoform. The models' own predictions on these genomes are in each model repository's annot_results/ folder.
  • The plant tutorial data: training and validation genomes with per-base labels, used by the genome-annotation notebooks of the ntv3 Space (03a training, 03b decoding, 03c evaluation).

Dataset organization

InstaDeepAI/NTv3_annot_dataset/
β”œβ”€β”€ <clade>/test_species/<assembly>/     # clade = mammals, plants or insects
β”‚   β”œβ”€β”€ genome.fa.gz                     # soft-masked genome, bgzipped
β”‚   β”œβ”€β”€ genome.fa.gz.fai                 # samtools faidx index
β”‚   β”œβ”€β”€ genome.fa.gz.gzi                 # bgzip index
β”‚   β”œβ”€β”€ reference_longest_isoform.gff3.gz
β”‚   β”œβ”€β”€ reference_all_isoforms.gff3.gz
β”‚   └── pseudogenes.bed
└── plants/
    β”œβ”€β”€ metadata.tsv                     # one row per tutorial species
    β”œβ”€β”€ class_counts.json
    β”œβ”€β”€ class_weights.json
    β”œβ”€β”€ train_species/<assembly>/        # genome.fa.gz(.fai, .gzi), labels.bed.gz
    β”œβ”€β”€ val_species/<assembly>/          # same as test species, plus labels.bed.gz,
    β”‚                                    #   without reference_all_isoforms.gff3.gz
    └── test_species/<assembly>/         # Medicago and Mimulus also carry labels.bed.gz;
                                         #   Medicago carries demo_log_probs/

Folders are named by assembly, as in the model repositories' annot_results/ files.

Files

  • genome.fa.gz: the soft-masked genome (repeats in lowercase), bgzipped, one record per sequence, record names cut to the sequence ID. For test species it is the complete assembly, every contig, with the sequence names of the reference annotation. Tutorial training and validation genomes keep only the contigs of at least 131,072 bp, the tutorial's training window.
  • reference_longest_isoform.gff3.gz: the reference the benchmark scores against. Protein-coding genes only, one transcript per gene (the one with the longest CDS), gene, mRNA and CDS rows, ID and Parent attributes only. 1-based closed coordinates (GFF3).
  • reference_all_isoforms.gff3.gz (test species): the same genes, with every transcript the source annotation release gives them, in the same format. A prediction that matches any transcript of a gene counts under the any-isoform rule. When the source release does not carry a reference transcript's exact CDS, that transcript is kept as well, so the file is a strict superset of the longest-isoform reference: 171 genes whose IDs were assigned when the longest isoform was extracted (agat-gene-*: 151 immune receptor gene segments in cow and whale, 15 chloroplast genes, 5 insect genes) and one transcript in cow (PEG10, ID suffixed .longest_isoform).
  • pseudogenes.bed: pseudogene regions of the source annotation that do not overlap a reference CDS. Predicted genes there are ignored when scoring. BED, 0-based half-open.
  • labels.bed.gz (tutorial species): the per-base training labels, one of 15 classes (intergenic, intron_p0-2, CDS_p0-2, splice_donor_p0-2, splice_acceptor_p0-2, start_codon, stop_codon), as BED runs per strand (chrom, start, end, class, ., strand), 0-based half-open.
  • plants/metadata.tsv: the tutorial species, their role (train, validation, test), tier (the tutorial's presets train on tiers 1-2), source, accession and the chromosome the tutorial evaluates on (eval_chromosomes).
  • plants/class_counts.json: per-species base counts of each class. Notebook 03a derives its loss weights from them, for the genomes it trains on.
  • plants/class_weights.json: those weights precomputed over all the training genomes (mean inverse class frequency).
  • demo_log_probs/ (Medicago): precomputed per-base log-probabilities of NTv3_annot_plants over NC_053042.1:11,010,048-12,582,912, decoded in notebook 03b; meta.json records the model, code revision, windows and hardware.

Scores are gene- and CDS-level F1: a predicted gene counts only if its whole CDS structure matches exactly, predicted genes with less than 201 nt of CDS are ignored, and so are those in pseudogenes.bed. Notebook 03c implements the evaluation.

Test species

Clade Folder Species Contigs Genes Transcripts Genome Reference annotation
mammals GCF_002263795.3_ARS-UCD2.0 Bos taurus (cow) 1,958 21,577 49,639 NCBI RefSeq NCBI RefSeq GCF_002263795.3-RS_2024_12
mammals GCF_002288925.2_ASM228892v3 Delphinapterus leucas (beluga whale) 5,905 18,389 40,864 NCBI RefSeq NCBI RefSeq Annotation Release 101
plants GCF_000005505.3_Brachypodium_distachyon_v3.0 Brachypodium distachyon 11 25,477 32,269 NCBI RefSeq NCBI RefSeq Annotation Release 103
plants EcalifornicavarOrangeKingHAP1v1.1 Eschscholzia californica 'Orange King' HAP1 6 29,562 42,970 Phytozome 828 Phytozome v1.1
plants FmultifloravarABG20040013HAP1v1.1 Freycinetia multiflora ABG20040013 HAP1 30 28,264 38,805 Phytozome 868 Phytozome v1.1
plants GCF_003473485.1_MtrunA17r5.0-ANR Medicago truncatula 42 31,794 37,660 NCBI RefSeq NCBI RefSeq GCF_003473485.1-RS_2025_04
plants MguttatusvarIM62v3.1 Mimulus guttatus IM62 23 25,096 31,078 Phytozome 797 Phytozome v3.1
insects GCF_030269925.1_ASM3026992v2 Bombyx mori 30 13,251 22,941 NCBI RefSeq NCBI RefSeq GCF_030269925.1-RS_2024_01
insects GCF_021464435.1_ULB_Chis1_1.0 Cataglyphis hispanica 453 10,380 17,463 NCBI RefSeq NCBI RefSeq Annotation Release 100
insects GCF_905220415.1_ilColCroc2.1 Colias croceus 32 13,364 18,775 NCBI RefSeq NCBI RefSeq Annotation Release 100
insects GCF_018135715.1_MEX_DaPlex Danaus plexippus 66 12,669 19,058 NCBI RefSeq NCBI RefSeq GCF_018135715.1-RS_2023_11
insects GCF_905404315.1_ilLepSina1.1 Leptidea sinapis 49 12,276 19,563 NCBI RefSeq NCBI RefSeq Annotation Release 100
insects GCF_905147045.1_ilAglIoxx1.1 Nymphalis io (syn. Aglais io) 41 12,024 18,680 NCBI RefSeq NCBI RefSeq Annotation Release 100
insects GCF_907164935.1_iOsmBic2.1 Osmia bicornis 441 11,262 18,822 NCBI RefSeq NCBI RefSeq Annotation Release 101
insects GCF_031307605.1_icTriCast1.1 Tribolium castaneum 149 11,953 19,088 NCBI RefSeq NCBI RefSeq GCF_031307605.1-RS_2024_04
insects GCF_905220365.1_ilVanCard2.1 Vanessa cardui 36 13,070 17,975 NCBI RefSeq NCBI RefSeq Annotation Release 100
insects GCF_012273895.1_Zerene_cesonia_1.1 Zerene cesonia 275 11,791 15,989 NCBI RefSeq NCBI RefSeq Annotation Release 100

Genes is the number of reference genes; Transcripts, the coding transcripts in reference_all_isoforms.gff3.gz. NCBI genomes are the _genomic.fna.gz of the assembly; the Phytozome genomes are its softmasked FASTA (Freycinetia: the 30 scaffolds of Phytozome 868 concatenated).

Plant tutorial species

Role Folder Species Source
train (tier 1) TAIR10 Arabidopsis thaliana Ensembl Plants (Araport11 genes)
train (tier 1) GCF_000004075.3_Cucumber_9930_V3 Cucumis sativus NCBI RefSeq
train (tier 1) GCF_022201045.2_DVS_A1.0 Citrus sinensis NCBI RefSeq
train (tier 1) GCF_019578655.1_ASM1957865v1 Ricinus communis NCBI RefSeq
train (tier 1) GCF_020921035.1_ASM2092103v1 Rhodamnia argentea NCBI RefSeq
train (tier 1) GCF_005286985.2_Setaria_viridis_v4.0 Setaria viridis NCBI RefSeq
train (tier 1) GCF_016808095.1_ASM1680809v1 Vigna angularis NCBI RefSeq
train (tier 1) GCF_030704535.1_ASM3070453v1 Vitis vinifera NCBI RefSeq
train (tier 2) GCF_031755915.1_ASM3175591v1 Ziziphus jujuba NCBI RefSeq
train (tier 2) GCF_018687715.1_C.illinoinensisPawnee_v1 Carya illinoinensis NCBI RefSeq
train (tier 2) GCF_036884655.1_Cavendish_Baxijiao_AAA Musa acuminata NCBI RefSeq
train (tier 2) GCF_958298935.1_lpPhrAust1.1 Phragmites australis NCBI RefSeq
train (tier 2) IRGSP-1.0 Oryza sativa Ensembl Plants genome, NCBI RefSeq genes
validation GCF_000002775.5_P.trichocarpa_v4.1 Populus trichocarpa NCBI RefSeq
validation Tlatifoliav1.1 Typha latifolia JGI (GenBank copy, GCA_059706395.1)
test GCF_003473485.1_MtrunA17r5.0-ANR Medicago truncatula see the test species table
test MguttatusvarIM62v3.1 Mimulus guttatus IM62 see the test species table

plants/metadata.tsv also lists tier 3-4 species; their files are not in this dataset.

Download

from huggingface_hub import hf_hub_download, snapshot_download

# One file
path = hf_hub_download(
    "InstaDeepAI/NTv3_annot_dataset",
    "mammals/test_species/GCF_002288925.2_ASM228892v3/reference_longest_isoform.gff3.gz",
    repo_type="dataset",
)

# One species
local_dir = snapshot_download(
    "InstaDeepAI/NTv3_annot_dataset",
    repo_type="dataset",
    allow_patterns="plants/test_species/GCF_003473485.1_MtrunA17r5.0-ANR/*",
)

Sources and licence

The files we derived (labels, class statistics, log-probabilities) are released under CC BY-NC 4.0. Genomes and reference annotations are redistributed from NCBI RefSeq, Ensembl Plants and JGI Phytozome under their own terms; please cite the original assemblies and annotations. The three Phytozome genomes are listed as unrestricted:

Citation

Citation to be added on publication.

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