diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 7e79b5a3..bc8ae63e 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -26,7 +26,11 @@ jobs: uses: actions/setup-python@v5 with: python-version: "3.10" - + - name: Set up Java + uses: actions/setup-java@v3 + with: + distribution: 'zulu' + java-version: '22' - name: Install dependencies run: | python -m pip install --upgrade pip @@ -42,7 +46,8 @@ jobs: run: | pytest --cov=casanovo tests/ - name: Upload coverage to codecov - uses: codecov/codecov-action@v3 + uses: codecov/codecov-action@v4 with: token: ${{ secrets.CODECOV_TOKEN }} fail_ci_if_error: true + \ No newline at end of file diff --git a/README.md b/README.md index 533c76e2..35b7c646 100644 --- a/README.md +++ b/README.md @@ -7,7 +7,7 @@ If you use Casanovo in your work, please cite the following publications: - Yilmaz, M., Fondrie, W. E., Bittremieux, W., Oh, S. & Noble, W. S. *De novo* mass spectrometry peptide sequencing with a transformer model. in *Proceedings of the 39th International Conference on Machine Learning - ICML '22* vol. 162 25514–25522 (PMLR, 2022). [https://proceedings.mlr.press/v162/yilmaz22a.html](https://proceedings.mlr.press/v162/yilmaz22a.html) -- Yilmaz, M., Fondrie, W. E., Bittremieux, W., Nelson, R., Ananth, V., Oh, S. & Noble, W. S. Sequence-to-sequence translation from mass spectra to peptides with a transformer model. in *bioRxiv* (2023). [doi:10.1101/2023.01.03.522621](https://doi.org/10.1101/2023.01.03.522621) +- Yilmaz, M., Fondrie, W. E., Bittremieux, W., Melendez, C.F., Nelson, R., Ananth, V., Oh, S. & Noble, W. S. Sequence-to-sequence translation from mass spectra to peptides with a transformer model. in *Nature Communications* **15**, 6427 (2024). [doi:10.1038/s41467-024-49731-x](https://doi.org/10.1038/s41467-024-49731-x) ## Documentation diff --git a/docs/images/help.svg b/docs/images/help.svg index baf2e237..80d63c7e 100644 --- a/docs/images/help.svg +++ b/docs/images/help.svg @@ -1,4 +1,4 @@ - + - - + + - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + - + - + - - $ casanovo --help + + $ casanovo --help + +Usage:casanovo [OPTIONS] COMMAND [ARGS]...                                     + + ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓  + ┃                                  Casanovo                                  ┃  + ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛  + Casanovo de novo sequences peptides from tandem mass spectra using a            + Transformer model. Casanovo currently supports mzML, mzXML, and MGF files for   + de novo sequencing and annotated MGF files, such as those from MassIVE-KB, for  + training new models.                                                            + + Links:                                                                          + + • Documentation: https://casanovo.readthedocs.io                               + • Official code repository: https://github.com/Noble-Lab/casanovo              + + If you use Casanovo in your work, please cite:                                  + + • Yilmaz, M., Fondrie, W. E., Bittremieux, W., Oh, S. & Noble, W. S. De novo   +mass spectrometry peptide sequencing with a transformer model. Proceedings   +of the 39th International Conference on Machine Learning - ICML '22 (2022)   +doi:10.1101/2022.02.07.479481.                                               + +╭─ Options ────────────────────────────────────────────────────────────────────╮ +│--help-h    Show this message and exit.                                    │ +╰──────────────────────────────────────────────────────────────────────────────╯ +╭─ Commands ───────────────────────────────────────────────────────────────────╮ +│configure Generate a Casanovo configuration file to customize.              │ +│evaluate  Evaluate de novo peptide sequencing performance.                  │ +│sequence  De novo sequence peptides from tandem mass spectra.               │ +│train     Train a Casanovo model on your own data.                          │ +│version   Get the Casanovo version information                              │ +╰──────────────────────────────────────────────────────────────────────────────╯ + diff --git a/docs/index.md b/docs/index.md index 943ea7d6..f0c5700f 100644 --- a/docs/index.md +++ b/docs/index.md @@ -7,7 +7,7 @@ If you use Casanovo in your work, please cite the following publications: - Yilmaz, M., Fondrie, W. E., Bittremieux, W., Oh, S. & Noble, W. S. *De novo* mass spectrometry peptide sequencing with a transformer model. in *Proceedings of the 39th International Conference on Machine Learning - ICML '22* vol. 162 25514–25522 (PMLR, 2022). [https://proceedings.mlr.press/v162/yilmaz22a.html](https://proceedings.mlr.press/v162/yilmaz22a.html) -- Yilmaz, M., Fondrie, W. E., Bittremieux, W., Nelson, R., Ananth, V., Oh, S. & Noble, W. S. Sequence-to-sequence translation from mass spectra to peptides with a transformer model. in *bioRxiv* (2023). [doi:10.1101/2023.01.03.522621](https://doi.org/10.1101/2023.01.03.522621) +- Yilmaz, M., Fondrie, W. E., Bittremieux, W., Melendez, C.F., Nelson, R., Ananth, V., Oh, S. & Noble, W. S. Sequence-to-sequence translation from mass spectra to peptides with a transformer model. in *Nature Communications* **15**, 6427 (2024). [doi:10.1038/s41467-024-49731-x](https://doi.org/10.1038/s41467-024-49731-x) ```{toctree} --- diff --git a/tests/jmzTabValidator.jar b/tests/jmzTabValidator.jar new file mode 100644 index 00000000..7e33d161 Binary files /dev/null and b/tests/jmzTabValidator.jar differ diff --git a/tests/test_integration.py b/tests/test_integration.py index e5d4b285..a622b188 100644 --- a/tests/test_integration.py +++ b/tests/test_integration.py @@ -1,4 +1,5 @@ import functools +import subprocess from pathlib import Path import pyteomics.mztab @@ -7,6 +8,9 @@ from casanovo import casanovo +TEST_DIR = Path(__file__).resolve().parent + + def test_train_and_run( mgf_small, mzml_small, tiny_config, tmp_path, monkeypatch ): @@ -50,7 +54,7 @@ def test_train_and_run( result = run(eval_args) assert result.exit_code == 0 - # Finally try predicting: + # Try predicting: output_filename = tmp_path / "test.mztab" predict_args = [ "sequence", @@ -86,6 +90,30 @@ def test_train_and_run( assert psms.loc[4, "sequence"] == "PEPTLDEK" assert psms.loc[4, "spectra_ref"] == "ms_run[2]:scan=111" + # Validate mztab output + validate_args = [ + "java", + "-jar", + f"{TEST_DIR}/jmzTabValidator.jar", + "--check", + f"inFile={output_filename}", + ] + + validate_result = subprocess.run( + validate_args, + stdout=subprocess.PIPE, + stderr=subprocess.PIPE, + text=True, + ) + + assert validate_result.returncode == 0 + assert not any( + [ + line.startswith("[Error-") + for line in validate_result.stdout.splitlines() + ] + ) + def test_auxilliary_cli(tmp_path, monkeypatch): """Test the secondary CLI commands"""