Simulation of Mass Spectrometry-based Proteomics Data with Synthedia

Overview

Journal Bioinform Adv

Publisher Oxford University Press

Specialty Biology

Date 2023 Jan 26

PMID 36698761

Authors

Michael G Leeming

Ching-Seng Ang

Shuai Nie

Swati Varshney

Nicholas A Williamson

Affiliations

Soon will be listed here.

Abstract

Motivation: A large number of experimental and bioinformatic parameters must be set to identify and quantify peptides in mass spectrometry experiments and each of these will impact the results. An ability to simulate raw data with known contents would allow researchers to rapidly explore the effects of varying experimental parameters and systematically investigate downstream processing software. A range of data simulators are available for established data-dependent acquisition methodologies, but these do not extend to the rapidly developing field of data-independent acquisition (DIA) strategies.

Results: Here, we present a software package to simulate DIA liquid chromatography-mass spectrometry for bottom-up proteomics experiments. Synthedia can generate datasets with known peptide precursor ions and fragments and allows for the customization of a wide variety of chromatographic and mass spectrometry parameters.

Availability And Implementation: Synthedia is freely available via the internet and can be used through a graphical website (https://synthedia.org/) or locally via the command line (https://github.com/mgleeming/synthedia/).

Supplementary Information: Supplementary data are available at online.

Citing Articles

Toward an Integrated Machine Learning Model of a Proteomics Experiment.

Neely B, Dorfer V, Martens L, Bludau I, Bouwmeester R, Degroeve S J Proteome Res. 2023; 22(3):681-696.

PMID: 36744821 PMC: 9990124. DOI: 10.1021/acs.jproteome.2c00711.

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