- Citation
- General
- Datasets
- Reproducibility
- Code structure
If you have found our manuscript useful in your work, please consider citing:
Engler Hart, C., Kind, T., Dorrestein, P. D., Healey, D., and Domingo-Fernández, D. (2024). Weighting low-intensity MS/MS ions and m/z frequency for spectral library annotation. Journal of the American Society for Mass Spectrometry.
This repository contains code for evaluating weighting methods for spectral similarity metrics.
Links to the specific files are given in the notebooks The dump of the processed files are available at https://doi.org/10.5281/zenodo.8417612 and the zip files should be unzipped at placed ./data with the following structure:
-- data
|-- modified_cosine_queries
|-- network_method
|-- nist
|-- Wout_data
To reproduce the results, run the notebooks in the given order.
- The Python virtual environment can be installed using Poetry.
- Install the spectral_entropy package from https://github.com/YuanyueLi/SpectralEntropy (this package is not available in PyPi).
The project has the following structure:
-- notebooks
|-- 1_spectral_aligment
|-- 1_benchmark_other_similarity_metrics.ipynb
|-- 1.1_benchmark_stats.ipynb
|-- 2_weighted_modified_cosine.ipynb
|-- 3_create_figures.ipynb
|-- 4_compare_scores.ipynb
|-- 5_some_weighted.ipynb
|-- benchmark.py
|-- 2_library_search
|-- 1_gnps_ppm.ipynb
|-- 2_query_library_example.ipynb
|-- 3_results_benchmark.ipynb
|-- 4_results_comparing_ppm_windows.ipynb
|-- query_library.py
-- src
|-- ms_similarity_metrics
├── __init__.py
├── create_spectrum.py
├── frequency.py
├── hash_utils.py
├── plot.py
├── query_pool.py
├── reformat_columns.py
└── version.py