SMITER—A Python Library for the Simulation of LC-MS/MS Experiments

Kösters, Manuel; Leufken, Johannes; Leidel, Sebastian A. (2021). SMITER—A Python Library for the Simulation of LC-MS/MS Experiments. Genes, 12(3), p. 396. MDPI 10.3390/genes12030396

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SMITER (Synthetic mzML writer) is a Python-based command-line tool designed to simulate liquid-chromatography-coupled tandem mass spectrometry LC-MS/MS runs. It enables the simulation of any biomolecule amenable to mass spectrometry (MS) since all calculations are based on chemical formulas. SMITER features a modular design, allowing for an easy implementation of different noise and fragmentation models. By default, SMITER uses an established noise model and offers several methods for peptide fragmentation, and two models for nucleoside fragmentation and one for lipid fragmentation. Due to the rich Python ecosystem, other modules, e.g., for retention time (RT) prediction, can easily be implemented for the tailored simulation of any molecule of choice. This facilitates the generation of defined gold-standard LC-MS/MS datasets for any type of experiment. Such gold standards, where the ground truth is known, are required in computational mass spectrometry to test new algorithms and to improve parameters of existing ones. Similarly, gold-standard datasets can be used to evaluate analytical challenges, e.g., by predicting co-elution and co-fragmentation of molecules. As these challenges hinder the detection or quantification of co-eluents, a comprehensive simulation can identify and thus, prevent such difficulties before performing actual MS experiments. SMITER allows the creation of such datasets easily, fast, and efficiently.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Department of Chemistry, Biochemistry and Pharmaceutical Sciences (DCBP)

Graduate School:

Graduate School for Cellular and Biomedical Sciences (GCB)

UniBE Contributor:

Kösters, Manuel, Leufken, Johannes, Leidel, Sebastian Andreas

Subjects:

500 Science > 570 Life sciences; biology
500 Science > 540 Chemistry

ISSN:

2073-4425

Publisher:

MDPI

Language:

English

Submitter:

Christina Schüpbach

Date Deposited:

06 Apr 2021 16:42

Last Modified:

07 Aug 2024 15:45

Publisher DOI:

10.3390/genes12030396

PubMed ID:

33799543

BORIS DOI:

10.48350/154021

URI:

https://boris.unibe.ch/id/eprint/154021

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