Taykhoom/insert-seq-glm-tang

GLM-Tang Task 5: INSERT-seq RNA Output

This dataset contains the reporter task used in Task 5 of Tang et al. Given a 173 nt transcribed insert, predict normalized total RNA output in mouse embryonic stem cells.

Loading

from datasets import load_dataset

dataset = load_dataset("Taykhoom/insert-seq-glm-tang")
train = dataset["train"]
validation = dataset["validation"]
test = dataset["test"]

Dataset size

Split	Rows
train	9,131
validation	1,149
test	1,137
Total	11,417

The Tang Results text reports 10,774 sequences, but the released HDF5 and Methods split counts contain 11,417. This release follows the distributed HDF5.

Sequence derivation

The public GEO FASTA contains 16,461 unique 175 nt records. Removing one base from each end gives the exact 173 nt HDF5 sequence:

sequence = geo_sequence[1:-1]

Every archived sequence maps uniquely to one GEO source row.

Most inserts are source-defined mm10 regions, while randomized controls are synthetic. Nullable source coordinates and explicit provenance distinguish the two cases.

Target contract

Direct row-wise matching to the GEO normalized table identifies the three HDF5 target columns:

1. totalRNA_average
2. runonRNA_average
3. sortseq_average

The released model does not train on raw total RNA. It uses:

label = log1p(totalRNA_average)

This transformed value is the model-facing label.

The raw and auxiliary assay values are retained as:

• raw_total_rna
• aux_target_run_on_rna
• aux_target_sort_seq

These are targets/measurements, not sequence features.

Columns

Column	Description
split	Released train, val, or test partition.
sequence	Exact 173 nt archived model input in transcribed orientation.
label	log1p(totalRNA_average), matching released training/evaluation code.
example_id	GEO FASTA sequence identifier.
source_index	Zero-based row index in the 16,461-row GEO FASTA/table.
raw_total_rna	Raw totalRNA_average assay value.
aux_target_run_on_rna	runonRNA_average.
aux_target_sort_seq	sortseq_average.
source_category, source_class, source_window, source_barcode	Supplementary Table 2 design provenance.
locus_group_id, split_leakage	Source name (unique-ID fallback for unnamed rows) and whether that group spans archived partitions.
chrom, start, end, strand, genome_build	Nullable source-provided zero-based, half-open GRCm38/mm10 coordinates.
coordinates_available	Whether all four source coordinate fields are present.
species	Always Mus musculus.
cell_type	Always mouse embryonic stem cell.
is_synthetic	True only for randomized_control rows.

The released code trains with mean-squared error and reports test Pearson correlation and MSE on label.

Reproduction boundary

The public source has 16,461 rows, while Tang's archive retains 11,417. The source-row selection rule and split seed were not released. This dataset therefore preserves archived row membership/order exactly rather than claiming to recreate that unpublished selection from all GEO rows.

All archived assay values equal an explicit float32 conversion of the GEO table values.

Supplementary Table 2 provides coordinates for 10,346 rows. The remaining 1,071 rows include 1,059 randomized controls and 12 non-synthetic mRNA-end rows with no published locus. Six source intervals span 172 bases even though the corresponding assay sequence is 173 nt; these values are preserved as source provenance rather than silently adjusted. No hg38 mapping is claimed.

The archived split contains 424 locus_group_id values in multiple partitions, affecting 848 rows. Group-aware evaluation should use locus_group_id and inspect split_leakage.

Processing and verification

The HDF5 byte check, GEO sequence matching, exact float32 target conversion, target transformation, split-order verification, and the root manifest contract are documented at stable repository links:

• Processing repository: https://github.com/TaykhoomDalal/GLM-Tang-Processing/tree/main
• Task documentation: https://github.com/TaykhoomDalal/GLM-Tang-Processing/blob/main/insert-seq/README.md
• Reproducibility manifest: https://github.com/TaykhoomDalal/GLM-Tang-Processing/blob/main/manifest.json

Sources and citation

Tang, Z. et al. Genome Biology 26, 203 (2025). https://doi.org/10.1186/s13059-025-03674-8

Vlaming, H., Mimoso, C. A., Field, A. R., Martin, B. J. & Adelman, K. Screening thousands of transcribed coding and non-coding regions reveals sequence determinants of RNA polymerase II elongation potential. Nature Structural & Molecular Biology 29, 613–620 (2022). https://doi.org/10.1038/s41594-022-00785-9

Source accession: GEO GSE178230.

License

The Tang archive is CC BY 4.0. GEO does not attach a standalone Creative Commons license to GSE178230; users must retain the accession/publication attribution and follow the source terms.