---
pretty_name: UltraMS MSnLib benchmark (formula-level split A + strict-adduct molecule-level split B)
license: cc-by-4.0
language:
  - en
size_categories:
  - 100K<n<1M
task_categories:
  - other
configs:
  - config_name: split_A_formula_split
    data_files: split_A_full_msnlib/formula_split.csv
  - config_name: split_A_row_formula_fold
    data_files: split_A_full_msnlib/row_formula_fold.csv
  - config_name: split_A_test_spectra
    data_files: split_A_full_msnlib/test_spectra.csv
  - config_name: split_A_val_spectra
    data_files: split_A_full_msnlib/val_spectra.csv
  - config_name: split_A_test_molecules_voting_official
    data_files: split_A_full_msnlib/test_molecules_voting.csv
  - config_name: split_A_test_molecules_voting_canonical_view
    data_files: split_A_full_msnlib/test_molecules_voting_canonical_view.csv
  - config_name: split_A_msnlib_rt
    data_files: split_A_full_msnlib/msnlib_rt.csv.gz
  - config_name: split_B_pos_compound_split
    data_files: splits/pos_compound_split.csv
  - config_name: split_B_neg_compound_split
    data_files: splits/neg_compound_split.csv
  - config_name: split_B_pos_val_queries
    data_files: queries/pos_val_queries.csv
  - config_name: split_B_pos_test_queries
    data_files: queries/pos_test_queries.csv
  - config_name: split_B_neg_val_queries
    data_files: queries/neg_val_queries.csv
  - config_name: split_B_neg_test_queries
    data_files: queries/neg_test_queries.csv
  - config_name: split_B_pos_val_library
    data_files: libraries/pos_val_library.csv
  - config_name: split_B_pos_test_library
    data_files: libraries/pos_test_library.csv
  - config_name: split_B_neg_val_library
    data_files: libraries/neg_val_library.csv
  - config_name: split_B_neg_test_library
    data_files: libraries/neg_test_library.csv
tags:
  - chemistry
  - mass-spectrometry
  - metabolomics
  - small-molecules
  - tandem-ms
  - spectrum-library-search
  - molecule-retrieval
  - benchmark
  - ultraMS
---

# UltraMS MSnLib benchmark

Zenodo DOI: [10.5281/zenodo.23963489](https://doi.org/10.5281/zenodo.23963489)

Two frozen, independent benchmark splits of the [MSnLib](https://doi.org/10.1038/s41592-025-02813-0)
tandem mass spectral library, released by UltraMS. The splits are different objects:

* **Split A — UltraMS MSnLib formula-level split** (all 560,084 spectra, all adducts):
  21,107 molecular formulas, split 16,885 / 2,110 / 2,112 formulas and
  446,667 / 55,980 / 57,437 spectra into train / validation / test. Formula-disjoint. Test
  fold: 57,437 spectra, 2,112 formulas, 5,003 source SMILES / 4,889 canonical molecules.
  Population for single-spectrum candidate ranking, multiple-spectrum voting, label-blind
  grouping, fingerprint prediction and embedding analyses (Figure 2b/2j, 3a/3b/3d/3g,
  3a_sp_4, 3a_sp_5, single-spectrum baselines). The **official multiple-spectrum voting
  units are the 5,002 MSnLib source-SMILES groups covering 57,436 spectra**
  (`test_molecules_voting.csv`); a canonical-SMILES alternative view (4,888 groups) is also
  provided (`test_molecules_voting_canonical_view.csv`). Per-spectrum retention times
  (`row_index, rt` in seconds) are in `msnlib_rt.csv.gz` for the label-blind grouping and
  multiple-spectrum voting analyses.
* **Split B — strict-adduct molecule-level split** (`[M+H]+` and `[M-H]-` only): 41,348 /
  21,293 compounds and 301,636 / 140,193 preprocessed spectra, split 70/15/15 per polarity
  by RDKit canonical isomeric SMILES, with frozen queries and libraries for
  spectrum-to-spectrum library search. Population for Figure 3e/3f/3h, 3h_sp_1 and the
  cross-collision-energy task (6,161 positive / 2,999 negative queries).

| split-B task | queries | library spectra | queries with an exact-adduct library positive |
| --- | ---: | ---: | ---: |
| `[M+H]+` test | 6,202 | 295,434 | 6,201 |
| `[M+H]+` validation | 6,202 | 250,424 | 6,194 |
| `[M-H]-` test | 3,193 | 137,000 | 3,160 |
| `[M-H]-` validation | 3,193 | 116,135 | 3,163 |

> **Disjointness.** Split A is formula-disjoint (no formula in two folds); split B is
> molecule-disjoint within each polarity (the train / validation / test compound sets are
> pairwise empty). The two splits must **not** be merged into a global-disjointness claim:
> about 41 % of split-B compounds lie in a different split-A fold, and a spectrum can be
> split-A test while its compound is split-B train. See the package
> `figures_mapping.md` §2 for the full cross-tabulation.

## Usage

```python
import pandas as pd

base = "https://huggingface.co/datasets/dsadd4/UltraMS-MSnLib-Benchmark/resolve/main/"

# split A — formula-level split of the full library
formulas = pd.read_csv(base + "split_A_full_msnlib/formula_split.csv")
rows = pd.read_csv(base + "split_A_full_msnlib/row_formula_fold.csv")      # 560,084 rows
test = pd.read_csv(base + "split_A_full_msnlib/test_spectra.csv")          # 57,437 rows
assert formulas.groupby("formula")["fold"].nunique().max() == 1

# split B — strict-adduct molecule-level library search
compound_split = pd.read_csv(base + "splits/pos_compound_split.csv")
queries = pd.read_csv(base + "queries/pos_test_queries.csv")
library = pd.read_csv(base + "libraries/pos_test_library.csv")

positives = library.groupby("canonical_isomeric_smiles").size()
n_pos = queries["canonical_isomeric_smiles"].map(positives).fillna(0).astype(int)
denominator = int((n_pos > 0).sum())      # 6,201
```

With `datasets` (one config per table, see the YAML header):

```python
from datasets import load_dataset
queries = load_dataset("dsadd4/UltraMS-MSnLib-Benchmark", "split_B_pos_test_queries", split="train")
```

Peak data are **not** part of the split tables. Every row is joined back to the spectra by
`row_index` / `msnlib_csv_data_row` / `first_msnlib_csv_data_row`, which point into
`MSnLib.csv`. `MSnLib.csv` and `MSnLib_candidates.json` are hosted in the same dataset; see
**Hosted files** below.

## Columns

* `split_A_full_msnlib/formula_split.csv`: `formula, fold, n_spectra`
* `split_A_full_msnlib/row_formula_fold.csv`: `row_index, formula, fold`
* `split_A_full_msnlib/{test,val}_spectra.csv`: `row_index, smiles, precursor_mz, adduct,
  collision_energy, fold, canonical_isomeric_smiles`
* `split_A_full_msnlib/test_molecules_voting.csv`: `group_id, smiles, n_spectra` —
  **official** voting units: 5,002 MSnLib-source-SMILES groups covering 57,436 spectra, the
  grouping of the published multiple-spectrum voting task (`n_molecules = 5002`)
* `split_A_full_msnlib/test_molecules_voting_canonical_view.csv`: `group_id,
  canonical_isomeric_smiles, n_spectra` — alternative canonical view: 4,888 groups covering
  the same 57,436 spectra
* `split_A_full_msnlib/msnlib_rt.csv.gz`: `row_index, rt` — per-spectrum retention time in
  seconds, aligned 1:1 to the `MSnLib.csv` data rows (560,084 rows)
* `splits/*_compound_split.csv`: `polarity, compound_id, canonical_isomeric_smiles, split,
  n_spectra, n_frozen_queries, n_raw_smiles_variants, first_msnlib_csv_data_row`
* `queries/*.csv`: `polarity, split, query_index, compound_id, canonical_isomeric_smiles,
  adduct, msnlib_csv_data_row, msnlib_csv_line, precursor_mz, n_peaks, collision_energy,
  source_smiles_raw, n_library_positives`
* `libraries/*.csv`: same as queries with `library_index` and `compound_split` instead of
  `query_index`; row order is the frozen library order

## Split-B evaluation protocol

1. Score every query against the complete library of its task (no candidate short list).
2. Correct = the top-1 library spectrum has the same canonical compound identity.
3. Empirical FDR = `(accepted − correct) / accepted`; identification recall =
   `correct / n_queries_with_library_positive` (6,201 / 3,160 for the two test tasks).
   Queries without a library positive enter the FDR denominator but not the recall
   denominator; `n_library_positives` is provided per query.
4. The test library contains all preprocessed spectra of the polarity except the selected
   test queries; the validation library contains train and validation compounds only.
5. Validation is for model selection only; evaluate the test fold once.

## Hosted files

The dataset hosts the complete manifest plus two large source files. Every file of the
manifest is checksummed in `SHA256SUMS`; the two large files are kept in a separate upload
step (see `hf_upload_commands.sh`, dry-run by default).

| hosted file | bytes | SHA-256 | purpose |
| --- | ---: | --- | --- |
| manifest: `split_A_full_msnlib/`, `splits/`, `queries/`, `libraries/`, `protocol/`, `rebuild/`, docs (59 files) | ≈ 185.2 MiB | see `SHA256SUMS` | the two benchmark splits, verifier, docs |
| `split_A_full_msnlib/msnlib_rt.csv.gz` | 1,483,069 | `994053612db874f7ac7985f278e04cc3463f3b93cd649a195bd167c4c6c7d3d8` | compact per-spectrum retention time (`row_index, rt` in seconds), aligned 1:1 to `MSnLib.csv`; used by the label-blind grouping analysis |
| `MSnLib.csv` | 752,707,651 | `be54b33039cf18675751ea3c6354b592177c899a0cd5df303ae616330133ec07` | full source CSV: one row per MSnLib spectrum (560,084 rows); every row pointer in the split tables resolves here |
| `MSnLib_candidates.json` | 1,368,264,026 | `125a1cdcc57a3fcef8cc76d5322ac0c434cd09b0bfb9e0c9d28bddf052f45fcc` | candidate SMILES lists behind the single-spectrum candidate-ranking task: a JSON object mapping a query SMILES string to its candidate SMILES list (9,886 query entries) |

`MSnLib.csv` is the UltraMS CSV conversion of the MSnLib original release (Zenodo
10.5281/zenodo.11163380, CC BY 4.0), whose 18 per-file MS2 JSONL record lists contain the
same 560,084 spectra. `MSnLib_candidates.json` contains candidate SMILES lists derived from
the MSnLib compound set; both files carry the MSnLib attribution.

## Provenance, verification, license

* Source rows: `MSnLib.csv` (560,084 rows) converted from the MSnLib original release
  (Brungs et al., CC BY 4.0; Zenodo 10.5281/zenodo.11163380).
* Hosted source files: `MSnLib.csv` (752,707,651 bytes, SHA-256 `be54b330…`) and
  `MSnLib_candidates.json` (1,368,264,026 bytes, SHA-256 `125a1cdc…`).
* Frozen split-B manifest, seeds 42 / 43, query seed 119; frozen split-A fold assignment
  from the `fold` column of `MSnLib.csv`.
* `SHA256SUMS` covers every file; `rebuild/verify_release.py` is a self-contained verifier
  that re-checks every count, ordering hash, disjointness statement, cross-split statistic
  and checksum offline.
* License **CC BY 4.0**, with attribution to MSnLib (CC BY 4.0); Apache-2.0 for the two
  UltraMS producer scripts. See the package `NOTICE.md`.

## Citation

```bibtex
@misc{ultrams_msnlib_benchmark_2026,
  title  = {UltraMS MSnLib benchmark: full-library formula-level split and strict-adduct molecule-level library-search split},
  author = {Li, Yifan and Zhong, Yunhua and Liu, Pan and Xia, Jun},
  year   = {2026},
  note   = {Derived from MSnLib (Brungs, Schmid, Pluskal; CC BY 4.0, Zenodo 10.5281/zenodo.11163380)},
  howpublished = {Hugging Face / Zenodo dataset, version 1.0.0}
}
```

Please also cite MSnLib (doi:10.1038/s41592-025-02813-0) and the UltraMS manuscript.