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bittremieux committed Jun 26, 2024
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9 changes: 8 additions & 1 deletion CHANGELOG.md
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- Precursor charges are now exported as integers instead of floats in the mzTab output file, in compliance with the mzTab specification.

## [4.2.1] - 2024-06-25

### Fixed

- Pin NumPy version to below v2.0 to ensure compatibility with current DepthCharge version.

## [4.2.0] - 2024-05-14

### Added
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- Initial Casanovo version.

[Unreleased]: https://github.com/Noble-Lab/casanovo/compare/v4.2.0...HEAD
[Unreleased]: https://github.com/Noble-Lab/casanovo/compare/v4.2.1...HEAD
[4.2.1]: https://github.com/Noble-Lab/casanovo/compare/v4.2.0...v4.2.1
[4.2.0]: https://github.com/Noble-Lab/casanovo/compare/v4.1.0...v4.2.0
[4.1.0]: https://github.com/Noble-Lab/casanovo/compare/v4.0.1...v4.1.0
[4.0.1]: https://github.com/Noble-Lab/casanovo/compare/v4.0.0...v4.0.1
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5 changes: 3 additions & 2 deletions docs/faq.md
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The [reported Casanovo results](https://doi.org/10.1101/2023.01.03.522621) were obtained by training on two different datasets: (i) a commonly used nine-species benchmark dataset, and (ii) a large-scale training dataset derived from the MassIVE Knowledge Base (MassIVE-KB).

All data for the _nine-species benchmark_ is available as annotated MGF files [on MassIVE](https://doi.org/doi:10.25345/C52V2CK8J).
All data for the _nine-species benchmark_ are available as annotated MGF files on MassIVE with [dataset identifier MSV000090982](https://doi.org/doi:10.25345/C52V2CK8J).
Annotated MGF files that are directly compatible with Casanovo are available in the `/MSV000090982/updates/2024-05-14_woutb_71950b89/peak/9speciesbenchmark` FTP directory.
Using these data, Casanovo was trained in a cross-validated fashion, training on eight species and testing on the remaining species.

The _MassIVE-KB training data_ was derived from PSMs used to compile the MassIVE-KB v1 spectral library and consists of 30 million PSMs.
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Using the filename (column "filename") you can then retrieve the corresponding peak files from the MassIVE FTP server and extract the desired spectra using their scan number (column "scan").

The _non-enzymatic dataset_, used to train a non-tryptic version of Casanovo, was created by selecting PSMs with a uniform distribution of amino acids at the C-terminal peptide positions from two datasets: MassIVE-KB and PROSPECT.
Training, validation, and test splits for the non-enzymatic dataset are available as annotated MGF files [on MassIVE](https://doi.org/doi:10.25345/C5KS6JG0W).
Training, validation, and test splits for the non-enzymatic dataset are available as annotated MGF files on MassIVE with [dataset identifier MSV000094014]](https://doi.org/doi:10.25345/C5KS6JG0W).

**How do I know which model to use after training Casanovo?**

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64 changes: 29 additions & 35 deletions docs/images/configure-help.svg
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