ViMMS 2.1.4

This is a minor release of ViMMS, bringing various enhancements and additions:

📌 New Features for Proteomics Support:

• Enhanced Scan Time Estimation: Improved estimations derived from actual experimental data.
• Isotope & Charge State Deconvolution: Initial support via ms_deisotope.
• Optuna Integration: Preliminary codes to optimize controller parameters using Optuna.
• OpenMS Peak Picking: Support added for box evaluation.

🛠 Improvements for Project Maintainability:

• Poetry Integration: Now using Poetry for dependency management and package building. Note: The Pipenv configuration file remains but will not be updated in future releases.
• Documentation Enhancements: Better documentation, including improvements to the Jekyll-based website.
• Matching Controller: Additional codes to support the controller, which is currently under development.

Thank you for using ViMMS and your continued support!

ViMMS 2.1.1

Minor speed improvement, about 10-20% faster from:

• Defaults to using fast chem set in the mass spec, which is slightly faster.
• Minor speed-up by removing unused attributes in Roi Builder
• Add an option not to generate the actual MS2 spectra. Useful when we care only which chemicals are fragmented, not how the generated MS2 spectra look like.

Tested with Python 3.10 and seems to work fine. Also incorporates the final analysis codes from DDAvsDIA comparison.

ViMMS 2.1.0

This is a release focused on speed, at least 2x simulation performance in the mass spec, and 2x from the ROI builder. This release sets the foundation where we can vectorise certain operations, rather than looping them.
Also incorporates some minor bugfixes. This is a potentially breaking change where old objects that have been pickled can no longer be unpickled in this version.

ViMMS 2.0.9

This is a release to support two new papers built on top of ViMMS.

The first paper describes the TopNEXt framework, an advanced multi-sample/-injections framework that allows us to easily build ROI-tracking controllers that considers ROI exclusion across samples.

The second paper describes how a framework like ViMMS can be used for a DDA-vs-DIA comparison, first in simulation and then in the actual machine.

Along the way we also introduced various bugfixes, new classes, stability improvements, etc.

ViMMS 2.0.5

This is a maintenance version which includes a major code clean-up and code restructuring. This release should be preferred over the older ones as the code quality here is significantly better.

You can also find the archived version of this release in Zenodo: .

Huge thanks to @MKoesters and @jspaezp for their valuable feedback as part of JOSS review process.

Changes:

• Improved API documentation at https://vimms.readthedocs.io.
• Improved README and Contributing guidelines.
• Improved class hierarchy, including proper uses of abstract classes.
• Added coverage report to CI
• Make project significantly more PEP8-compliant.
• Fixed broken example and demo notebooks.
• Moved old, unused or experimental files into their own old_unused_experimental branch.
• Restructuring of box controllers (WIP).
• Better evaluation methods (WIP).
• Starting work on DDA vs DIA comparison (WIP)

ViMMS 2.0.3

Minor updates including various bugfixes to the framework, tidying up the unit tests and API documentations in preparation for JOSS paper submission on ViMMS 2.0 framework.

ViMMS 2.0.0

This release of ViMMS contains many major changes, enhancements and features to accompany the paper 'Rapid Development of Improved Data-dependent Acquisition Strategies' (link to paper).
Here are some highlights of this release:

• Added supports to allow controllers to run on both the simulated environment as well as on an actual mass spectrometry. At the moment, we only support Thermo Fusion instrument on IAPI.
• Many new controllers, including the SmartROI and WeightedDEW controllers featured in the paper. These controllers outperform standard Top-N controllers in coverage, fragmenting more precursor ions that were missed before. For example usage, see these notebooks.
• Sequence managers and multi-sample methods. For example, see these notebooks.
• Many unit tests have been written to ensure robust codes. They can also be used to demonstrate how to run things in the simulated environment. See here.

Note: You can download ViMMS 1.0 used in our original paper from here. It contains codes up to the first paper, but they are quite out-of-date now.