Boosting the speed and accuracy of protein quantification algorithms in mass spectrometry-based proteomics

Pham, T. V.; Tran, C. T.; Henneman, A. A.; Pham, L. H.; Le, D. G.; Can, A. H.; Bui, P. H.; Piersma, S. R.; Jimenez, C. R.

doi:10.1101/2025.10.06.680769

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bioRxiv · 10.1101/2025.10.06.680769

Boosting the speed and accuracy of protein quantification algorithms in mass spectrometry-based proteomics

Pham, T. V.·Tran, C. T.·Henneman, A. A.·Pham, L. H.·Le, D. G.·Can, A. H.·Bui, P. H.·Piersma, S. R.·Jimenez, C. R.

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Abstract

Current methods for protein level quantification in mass spectrometry-based proteomics do not scale with the increasing number of samples because of limited system memory and algorithmic complexities. Here we propose a new data structure that supports parsing of input as data stream, improve state of the art quantitation methods in performance by orders of magnitudes, and provide a generic method to boost the precision and accuracy by fragment weighting.

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Pham, T. V., Tran, C. T., Henneman, A. A., Pham, L. H., Le, D. G., Can, A. H., Bui, P. H., Piersma, S. R., Jimenez, C. R.. 2025-10-08. Boosting the speed and accuracy of protein quantification algorithms in mass spectrometry-based proteomics. https://doi.org/10.1101/2025.10.06.680769

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