| Name | ms2rescore JSON |
| Version |
3.2.0.post1
JSON |
| download |
| home_page | None |
| Summary | Modular and user-friendly platform for AI-assisted rescoring of peptide identifications. |
| upload_time | 2025-10-22 13:24:30 |
| maintainer | None |
| docs_url | None |
| author | Ralf Gabriels, Arthur Declercq, Ana Sílvia C. Silva, Robbin Bouwmeester, Louise Buur |
| requires_python | >=3.10 |
| license | Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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| keywords |
ms2rescore
ms2pip
deeplc
percolator
proteomics
mass spectrometry
peptide identification
rescoring
machine learning
|
| VCS |
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<img src="https://github.com/compomics/ms2rescore/raw/main/img/ms2rescore_logo.png" width="150" height="150" alt="MS²Rescore"/>
<br/><br/>
[](https://github.com/compomics/ms2rescore/releases)
[](https://pypi.org/project/ms2rescore/)
[](https://github.com/compomics/ms2rescore/actions/)
[](https://github.com/compomics/ms2rescore/issues)
[](https://www.apache.org/licenses/LICENSE-2.0)
[](https://github.com/compomics/ms2rescore/commits/)
Modular and user-friendly platform for AI-assisted rescoring of peptide identifications
## About MS²Rescore
MS²Rescore performs ultra-sensitive peptide identification rescoring with LC-MS predictors such as
[MS²PIP][ms2pip] and [DeepLC][deeplc], and with ML-driven rescoring engines
[Percolator][percolator] or [Mokapot][mokapot]. This results in more confident peptide
identifications, which allows you to get **more peptide IDs** at the same false discovery rate
(FDR) threshold, or to set a **more stringent FDR threshold** while still retaining a similar
number of peptide IDs. MS²Rescore is **ideal for challenging proteomics identification workflows**,
such as proteogenomics, metaproteomics, or immunopeptidomics.
MS²Rescore can read peptide identifications in any format supported by [psm_utils][psm_utils]
(see [Supported file formats][file-formats]) and has been tested with various search engines output
files:
- [MS Amanda](http://ms.imp.ac.at/?goto=msamanda) `.csv`
- [Sage](https://github.com/lazear/sage) `.sage.tsv`
- [PeptideShaker](https://compomics.github.io/projects/peptide-shaker.html) `.mzid`
- [ProteomeDiscoverer](#)`.msf`
- [MSGFPlus](https://omics.pnl.gov/software/ms-gf) `.mzid`
- [Mascot](https://www.matrixscience.com/) `.mzid`
- [MaxQuant](https://www.maxquant.org/) `msms.txt`
- [X!Tandem](https://www.thegpm.org/tandem/) `.xml`
- [PEAKS](https://www.bioinfor.com/peaksdb/) `.mzid`
MS²Rescore is available as a [desktop application][desktop], a [command line tool][cli], and a
[modular Python API][python-package].
## TIMS²Rescore: Direct support for DDA-PASEF data
MS²Rescore v3.1+ includes TIMS²Rescore, a usage mode with specialized default configurations for
DDA-PASEF data from timsTOF instruments. TIMS²Rescore makes use of new MS²PIP prediction models for
timsTOF fragmentation and IM2Deep for ion mobility separation. Bruker .d and miniTDF spectrum
files are directly supported through the [timsrust](https://github.com/MannLabs/timsrust) library.
Checkout our [paper](https://doi.org/10.1021/acs.jproteome.4c00609) for more information and the
[TIMS²Rescore documentation][tims2rescore] to get started.
## Citing
**Latest MS²Rescore publication:**
> **MS²Rescore 3.0 is a modular, flexible, and user-friendly platform to boost peptide identifications, as showcased with MS Amanda 3.0.**
> Louise Marie Buur*, Arthur Declercq*, Marina Strobl, Robbin Bouwmeester, Sven Degroeve, Lennart Martens, Viktoria Dorfer*, and Ralf Gabriels*.
> _Journal of Proteome Research_ (2024) [doi:10.1021/acs.jproteome.3c00785](https://doi.org/10.1021/acs.jproteome.3c00785) <br/> \*contributed equally <span class="__dimensions_badge_embed__" data-doi="10.1021/acs.jproteome.3c00785" data-hide-zero-citations="true" data-style="small_rectangle"></span>
**MS²Rescore for immunopeptidomics:**
> **MS²Rescore: Data-driven rescoring dramatically boosts immunopeptide identification rates.**
> Arthur Declercq, Robbin Bouwmeester, Aurélie Hirschler, Christine Carapito, Sven Degroeve, Lennart Martens, and Ralf Gabriels.
> _Molecular & Cellular Proteomics_ (2021) [doi:10.1016/j.mcpro.2022.100266](https://doi.org/10.1016/j.mcpro.2022.100266) <span class="__dimensions_badge_embed__" data-doi="10.1016/j.mcpro.2022.100266" data-hide-zero-citations="true" data-style="small_rectangle"></span>
**MS²Rescore for timsTOF DDA-PASEF data:**
> **TIMS²Rescore: A DDA-PASEF optimized data-driven rescoring pipeline based on MS²Rescore.**
> Arthur Declercq*, Robbe Devreese*, Jonas Scheid, Caroline Jachmann, Tim Van Den Bossche, Annica Preikschat, David Gomez-Zepeda, Jeewan Babu Rijal, Aurélie Hirschler, Jonathan R Krieger, Tharan Srikumar, George Rosenberger, Dennis Trede, Christine Carapito, Stefan Tenzer, Juliane S Walz, Sven Degroeve, Robbin Bouwmeester, Lennart Martens, and Ralf Gabriels.
> _Journal of Proteome Research_ (2025) [doi:10.1021/acs.jproteome.4c00609](https://doi.org/10.1021/acs.jproteome.4c00609) <span class="__dimensions_badge_embed__" data-doi="10.1021/acs.jproteome.4c00609" data-hide-zero-citations="true" data-style="small_rectangle"></span>
**Original publication describing the concept of rescoring with predicted spectra:**
> **Accurate peptide fragmentation predictions allow data driven approaches to replace and improve upon proteomics search engine scoring functions.**
> Ana S C Silva, Robbin Bouwmeester, Lennart Martens, and Sven Degroeve.
> _Bioinformatics_ (2019) [doi:10.1093/bioinformatics/btz383](https://doi.org/10.1093/bioinformatics/btz383) <span class="__dimensions_badge_embed__" data-doi="10.1093/bioinformatics/btz383" data-hide-zero-citations="true" data-style="small_rectangle"></span>
To replicate the experiments described in this article, check out the
[publication branch][publication-branch] of the repository.
## Getting started
The desktop application can be installed on Windows with a [one-click installer][desktop-installer].
The Python package and command line interface can be installed with `pip`, `conda`, or `docker`.
Check out the [full documentation][docs] to get started.
## Questions or issues?
Have questions on how to apply MS²Rescore on your data? Or ran into issues while using MS²Rescore?
Post your questions on the [GitHub Discussions][discussions] forum and we are happy to help!
## How to contribute
Bugs, questions or suggestions? Feel free to post an issue in the [issue tracker][issues] or to
make a [pull request][pr]!
[docs]: https://ms2rescore.readthedocs.io/
[issues]: https://github.com/compomics/ms2rescore/issues/
[discussions]: https://github.com/compomics/ms2rescore/discussions/
[pr]: https://github.com/compomics/ms2rescore/pulls/
[desktop]: https://ms2rescore.readthedocs.io/en/stable/gui/
[desktop-installer]: https://github.com/compomics/ms2rescore/releases/latest
[cli]: https://ms2rescore.readthedocs.io/en/stable/cli/
[python-package]: https://ms2rescore.readthedocs.io/en/stable/api/ms2rescore/
[docker]: https://ms2rescore.readthedocs.io/en/stable/installation#docker-container
[publication-branch]: https://github.com/compomics/ms2rescore/tree/pub
[ms2pip]: https://github.com/compomics/ms2pip
[deeplc]: https://github.com/compomics/deeplc
[percolator]: https://github.com/percolator/percolator/
[mokapot]: https://mokapot.readthedocs.io/
[psm_utils]: https://github.com/compomics/psm_utils
[file-formats]: https://psm-utils.readthedocs.io/en/stable/#supported-file-formats
[tims2rescore]: https://ms2rescore.readthedocs.io/en/stable/userguide/tims2Rescore
Raw data
{
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"name": "ms2rescore",
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"requires_python": ">=3.10",
"maintainer_email": null,
"keywords": "MS2Rescore, MS2PIP, DeepLC, Percolator, proteomics, mass spectrometry, peptide identification, rescoring, machine learning",
"author": "Ralf Gabriels, Arthur Declercq, Ana S\u00edlvia C. Silva, Robbin Bouwmeester, Louise Buur",
"author_email": "Ralf Gabriels <ralf@gabriels.dev>, Arthur Declercq <arthur.declercq@ugent.be>",
"download_url": "https://files.pythonhosted.org/packages/4b/ca/ef821cb290794a78683e324ca2a6b94f03231f5898223198afafb6e79f58/ms2rescore-3.2.0.post1.tar.gz",
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"description": "<img src=\"https://github.com/compomics/ms2rescore/raw/main/img/ms2rescore_logo.png\" width=\"150\" height=\"150\" alt=\"MS\u00b2Rescore\"/>\n<br/><br/>\n\n[](https://github.com/compomics/ms2rescore/releases)\n[](https://pypi.org/project/ms2rescore/)\n[](https://github.com/compomics/ms2rescore/actions/)\n[](https://github.com/compomics/ms2rescore/issues)\n[](https://www.apache.org/licenses/LICENSE-2.0)\n[](https://github.com/compomics/ms2rescore/commits/)\n\nModular and user-friendly platform for AI-assisted rescoring of peptide identifications\n\n## About MS\u00b2Rescore\n\nMS\u00b2Rescore performs ultra-sensitive peptide identification rescoring with LC-MS predictors such as\n[MS\u00b2PIP][ms2pip] and [DeepLC][deeplc], and with ML-driven rescoring engines\n[Percolator][percolator] or [Mokapot][mokapot]. This results in more confident peptide\nidentifications, which allows you to get **more peptide IDs** at the same false discovery rate\n(FDR) threshold, or to set a **more stringent FDR threshold** while still retaining a similar\nnumber of peptide IDs. MS\u00b2Rescore is **ideal for challenging proteomics identification workflows**,\nsuch as proteogenomics, metaproteomics, or immunopeptidomics.\n\n\n\nMS\u00b2Rescore can read peptide identifications in any format supported by [psm_utils][psm_utils]\n(see [Supported file formats][file-formats]) and has been tested with various search engines output\nfiles:\n\n- [MS Amanda](http://ms.imp.ac.at/?goto=msamanda) `.csv`\n- [Sage](https://github.com/lazear/sage) `.sage.tsv`\n- [PeptideShaker](https://compomics.github.io/projects/peptide-shaker.html) `.mzid`\n- [ProteomeDiscoverer](#)`.msf`\n- [MSGFPlus](https://omics.pnl.gov/software/ms-gf) `.mzid`\n- [Mascot](https://www.matrixscience.com/) `.mzid`\n- [MaxQuant](https://www.maxquant.org/) `msms.txt`\n- [X!Tandem](https://www.thegpm.org/tandem/) `.xml`\n- [PEAKS](https://www.bioinfor.com/peaksdb/) `.mzid`\n\nMS\u00b2Rescore is available as a [desktop application][desktop], a [command line tool][cli], and a\n[modular Python API][python-package].\n\n## TIMS\u00b2Rescore: Direct support for DDA-PASEF data\n\nMS\u00b2Rescore v3.1+ includes TIMS\u00b2Rescore, a usage mode with specialized default configurations for\nDDA-PASEF data from timsTOF instruments. TIMS\u00b2Rescore makes use of new MS\u00b2PIP prediction models for\ntimsTOF fragmentation and IM2Deep for ion mobility separation. Bruker .d and miniTDF spectrum\nfiles are directly supported through the [timsrust](https://github.com/MannLabs/timsrust) library.\n\nCheckout our [paper](https://doi.org/10.1021/acs.jproteome.4c00609) for more information and the\n[TIMS\u00b2Rescore documentation][tims2rescore] to get started.\n\n## Citing\n\n**Latest MS\u00b2Rescore publication:**\n\n> **MS\u00b2Rescore 3.0 is a modular, flexible, and user-friendly platform to boost peptide identifications, as showcased with MS Amanda 3.0.**\n> Louise Marie Buur*, Arthur Declercq*, Marina Strobl, Robbin Bouwmeester, Sven Degroeve, Lennart Martens, Viktoria Dorfer*, and Ralf Gabriels*.\n> _Journal of Proteome Research_ (2024) [doi:10.1021/acs.jproteome.3c00785](https://doi.org/10.1021/acs.jproteome.3c00785) <br/> \\*contributed equally <span class=\"__dimensions_badge_embed__\" data-doi=\"10.1021/acs.jproteome.3c00785\" data-hide-zero-citations=\"true\" data-style=\"small_rectangle\"></span>\n\n**MS\u00b2Rescore for immunopeptidomics:**\n\n> **MS\u00b2Rescore: Data-driven rescoring dramatically boosts immunopeptide identification rates.**\n> Arthur Declercq, Robbin Bouwmeester, Aur\u00e9lie Hirschler, Christine Carapito, Sven Degroeve, Lennart Martens, and Ralf Gabriels.\n> _Molecular & Cellular Proteomics_ (2021) [doi:10.1016/j.mcpro.2022.100266](https://doi.org/10.1016/j.mcpro.2022.100266) <span class=\"__dimensions_badge_embed__\" data-doi=\"10.1016/j.mcpro.2022.100266\" data-hide-zero-citations=\"true\" data-style=\"small_rectangle\"></span>\n\n**MS\u00b2Rescore for timsTOF DDA-PASEF data:**\n\n> **TIMS\u00b2Rescore: A DDA-PASEF optimized data-driven rescoring pipeline based on MS\u00b2Rescore.**\n> Arthur Declercq*, Robbe Devreese*, Jonas Scheid, Caroline Jachmann, Tim Van Den Bossche, Annica Preikschat, David Gomez-Zepeda, Jeewan Babu Rijal, Aur\u00e9lie Hirschler, Jonathan R Krieger, Tharan Srikumar, George Rosenberger, Dennis Trede, Christine Carapito, Stefan Tenzer, Juliane S Walz, Sven Degroeve, Robbin Bouwmeester, Lennart Martens, and Ralf Gabriels.\n> _Journal of Proteome Research_ (2025) [doi:10.1021/acs.jproteome.4c00609](https://doi.org/10.1021/acs.jproteome.4c00609) <span class=\"__dimensions_badge_embed__\" data-doi=\"10.1021/acs.jproteome.4c00609\" data-hide-zero-citations=\"true\" data-style=\"small_rectangle\"></span>\n\n**Original publication describing the concept of rescoring with predicted spectra:**\n\n> **Accurate peptide fragmentation predictions allow data driven approaches to replace and improve upon proteomics search engine scoring functions.**\n> Ana S C Silva, Robbin Bouwmeester, Lennart Martens, and Sven Degroeve.\n> _Bioinformatics_ (2019) [doi:10.1093/bioinformatics/btz383](https://doi.org/10.1093/bioinformatics/btz383) <span class=\"__dimensions_badge_embed__\" data-doi=\"10.1093/bioinformatics/btz383\" data-hide-zero-citations=\"true\" data-style=\"small_rectangle\"></span>\n\nTo replicate the experiments described in this article, check out the\n[publication branch][publication-branch] of the repository.\n\n## Getting started\n\nThe desktop application can be installed on Windows with a [one-click installer][desktop-installer].\nThe Python package and command line interface can be installed with `pip`, `conda`, or `docker`.\nCheck out the [full documentation][docs] to get started.\n\n## Questions or issues?\n\nHave questions on how to apply MS\u00b2Rescore on your data? Or ran into issues while using MS\u00b2Rescore?\nPost your questions on the [GitHub Discussions][discussions] forum and we are happy to help!\n\n## How to contribute\n\nBugs, questions or suggestions? Feel free to post an issue in the [issue tracker][issues] or to\nmake a [pull request][pr]!\n\n[docs]: https://ms2rescore.readthedocs.io/\n[issues]: https://github.com/compomics/ms2rescore/issues/\n[discussions]: https://github.com/compomics/ms2rescore/discussions/\n[pr]: https://github.com/compomics/ms2rescore/pulls/\n[desktop]: https://ms2rescore.readthedocs.io/en/stable/gui/\n[desktop-installer]: https://github.com/compomics/ms2rescore/releases/latest\n[cli]: https://ms2rescore.readthedocs.io/en/stable/cli/\n[python-package]: https://ms2rescore.readthedocs.io/en/stable/api/ms2rescore/\n[docker]: https://ms2rescore.readthedocs.io/en/stable/installation#docker-container\n[publication-branch]: https://github.com/compomics/ms2rescore/tree/pub\n[ms2pip]: https://github.com/compomics/ms2pip\n[deeplc]: https://github.com/compomics/deeplc\n[percolator]: https://github.com/percolator/percolator/\n[mokapot]: https://mokapot.readthedocs.io/\n[psm_utils]: https://github.com/compomics/psm_utils\n[file-formats]: https://psm-utils.readthedocs.io/en/stable/#supported-file-formats\n[tims2rescore]: https://ms2rescore.readthedocs.io/en/stable/userguide/tims2Rescore\n",
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