Releases: Noble-Lab/casanovo
Releases · Noble-Lab/casanovo
Casanovo v5.1.2
5.1.2 - 2025-12-11
Changed
- Hotfix to ensure compatibility with PyTorch v2.6 when loading weights files.
Casanovo v5.1.1
5.1.1 - 2025-11-27
Changed
- Hotfix to avoid excessively slow peptide parsing during mzTab export.
Casanovo v5.1.0
5.1.0 - 2025-10-22
Changed
- Avoid redundant spectrum encoding during database mode to speed up PSM scoring.
accelerator: "auto"is overwritten toaccelerator: "cpu"on Apple Silicon devices due to MPS compatibility issues.- Removed
reverse_peptidesfrom the configuration since decoding from the C-terminus to the N-terminus yields better results. - Log a warning if residues in the user configuration are not present in the tokenizer alphabet.
- The full ProForma sequences of predicted peptides are reported in the
op_ms_run[1]_proformaof the output MzTab file for backwards compatibility.
Fixed
- Inline mass modifications are now specified separately from the
sequencecolumn in themodificationscolumn of the output mzTab file, as per the mzTab specification.
Casanovo v5.0.0
5.0.0 - 2025-07-09
Added
- Casanovo-DB mode (
casanovo db_search) to use Casanovo as a learned score function for sequence database searching (given a FASTA protein database). - During training, model checkpoints will be saved at the end of each training epoch in addition to the checkpoints saved at the end of every validation run.
- Besides as a local file, model weights can be specified from a URL. Upon initial download, the weights file is cached for future re-use.
- Training and optimizer metrics can be logged to a CSV file by setting the
log_metricsconfig file option to true. The CSV file will be written to under a sub-directory of the output directory namedcsv_logs. - New configuration options for detailed control of the gradients during training (gradient accumulation, clipping).
- New configuration option
min_peaksto discard low-quality spectra with too few peaks.
Changed
- Removed the
evaluatesub-command, and all model evaluation functionality has been moved to thesequencecommand using the new--evaluateflag. - The
--outputoption has been split into two options,--output_dirand--output_root. - The path suffix (extension) of
--output_rootwill no longer be removed as it was with the old--outputoption. - The
--validation_peak_pathis now optional when training; if--validation_peak_pathis not set then thetrain_peak_pathwill also be used for validation. - The
tb_summarywriterconfig option is now a boolean config option, and if set to true the TensorBoard summary will be written to a sub-directory of the output directory namedtensorboard. - Input peak files can now be specified as both individual file(s) and a directory.
- Peptidoforms are specified using ProForma 2.0 notation by default.
- DepthCharge is upgraded to the latest version 0.4.8.
- The product of the raw amino acid scores is used as the peptide score, rather then the arithmetic mean.
- Amino acid scores are directly reported, rather than averaged with the peptide score.
- The amino acid-level score of stand-alone N-terminal modifications is combined with that of the leading N-terminal residue.
- Renamed the
n_peaksconfiguration option of the maximum number of peaks to retain in a spectrum tomax_peaks. - Beam search decoding has been optimized for computational efficiency, achieving increased prediction speed.
Fixed
- Precursor charges are exported as integers instead of floats in the mzTab output file, in compliance with the mzTab specification.
- Fixed log entries written to the config file instead of the log file when running the
configurecommand.
Removed
- Removed the
save_top_koption from the Casanovo config, the model with the lowest validation loss during training will now be saved to a fixed filename<output_root>.best.ckpt. - The
model_save_folder_pathconfig option has been removed; model checkpoints will now be saved to--output_dirduring training.
Casanovo v4.3.0
4.3.0 - 2024-12-13
Fixed
- Amino acid scores in the mzTab output were reported in reversed order.
Casanovo v4.2.1
4.2.1 - 2024-06-25
Fixed
- Pin NumPy version to below v2.0 to ensure compatibility with current DepthCharge version.
Casanovo v4.2.0
4.2.0 - 2024-05-14
Added
- A deprecation warning will be issued when deprecated config options are used in the config file or in the model weights file.
Changed
- Config option
max_itershas been renamed tocosine_schedule_period_itersto better reflect that it controls the number of iterations for the cosine half period of the learning rate.
Fixed
- Fix beam search caching failure when multiple beams have an equal predicted peptide score by breaking ties randomly.
- The mzTab output file now has proper line endings regardless of platform, fixing the extra
\rfound when run on Windows.
Casanovo v4.1.0
4.1.0 - 2024-02-16
Changed
- Instead of having to specify
train_from_scratchin the config file, training will proceed from an existing model weights file if this is given as an argument tocasanovo train.
Fixed
- Fixed beam search decoding error due to non-deterministic selection of beams with equal scores.
Casanovo v4.0.1
4.0.1 - 2023-12-25
Fixed
- Fix automatic PyPI upload.
Casanovo v4.0.0
4.0.0 - 2023-12-22
Added
- Checkpoints include model parameters, allowing for mismatches with the provided configuration file.
acceleratorparameter controls the accelerator (CPU, GPU, etc) that is used.devicesparameter controls the number of accelerators used.val_check_intervalparameter controls the frequency of both validation epochs and model checkpointing during training.train_label_smoothingparameter controls the amount of label smoothing applied when calculating the training loss.
Changed
- The CLI has been overhauled to use subcommands.
- Upgraded to Lightning >=2.0.
- Checkpointing is configured to save the top-k models instead of all.
- Log steps rather than epochs as units of progress during training.
- Validation performance metrics are logged (and added to tensorboard) at the validation epoch, and training loss is logged at the end of training epoch, i.e. training and validation metrics are logged asynchronously.
- Irrelevant warning messages on the console output and in the log file are no longer shown.
- Nicely format logged warnings.
every_n_train_stepshas been renamed toval_check_intervalin accordance to the corresponding Pytorch Lightning parameter.- Training batches are randomly shuffled.
- Upgraded to Torch >=2.1.
Removed
- Remove config option for a custom Pytorch Lightning logger.
- Remove superfluous
custom_encoderconfig option.
Fixed
- Casanovo runs on CPU and can pass all tests.
- Correctly refer to input peak files by their full file path.
- Specifying custom residues to retrain Casanovo is now possible.
- Upgrade to depthcharge v0.2.3 to fix sinusoidal encoding and for the
PeptideTransformerDecoderhotfix. - Correctly report amino acid precision and recall during validation.