MaSS‐Simulator: A Highly Configurable Simulator for Generating MS/MS Datasets for Benchmarking of Proteomics Algorithms

Abstract

Mass Spectrometry (MS)-based proteomics has become an essential tool in the study of proteins. With the advent of modern MS machines huge amounts of data is being generated, which can only be processed by novel algorithmic tools. However, in the absence of data benchmarks and ground truth datasets algorithmic integrity testing and reproducibility is a challenging problem. To this end, MaSS-Simulator has been presented, which is an easy to use simulator and can be configured to simulate MS/MS datasets for a wide variety of conditions with known ground truths. MaSS-Simulator offers many configuration options to allow the user a great degree of control over the test datasets, which can enable rigorous and large- scale testing of any proteomics algorithm. MaSS-Simulator is assessed by comparing its performance against experimentally generated spectra and spectra obtained from NIST collections of spectral library. The results show that MaSS-Simulator generated spectra match closely with real-spectra and have a relative-error distribution centered around 25%. In contrast, the theoretical spectra for same peptides have relative-error distribution centered around 150%. MaSS-Simulator will enable developers to specifically highlight the capabilities of their algorithms and provide a strong proof of any pitfalls they might face. Source code, executables, and a user manual for MaSS-Simulator can be downloaded from https://github.com/pcdslab/MaSS-Simulator.

In-silico Optimisation of Mass Spectrometry Fragmentation Strategies in Metabolomics

“…To investigate the instrument performance with differing Top-N and dynamic exclusion windows, filters such as intensity threshold and monoisotopic peak determination were not used. This allowed for a consistent number tandem MS scans to be acquired under varying Top-N parameters and dynamic exclusion window (DEW), for N = (1,2,3,4,5,10,15,20,35,50) and DEW = (15,30,60,120). Ions were isolated with 0.7 m/z width and fragmented with fixed HCD collision energy of 25%.…”

“…Unlike other simulators, e.g. [14,16,15,4,3], chemical objects can also be associated with fragment spectra that could themselves be extracted from spectral databases or generated using in-silico fragment prediction methods (Section 2.2.5). In-silico scan simulation in ViMMS (yellow box in Figure 1) proceeds as follows.…”

“…Based on the MS level of the previous scan, as well as that of the scan about to be undertaken, the time for the scan about to take place is drawn from the times of those scans in the database which represent the relevant scan transition. 3 Scan times sampled in this manner will almost always not correspond to values observed in the original files from which the ROIs were extracted. This causes some difficulty with determining the intensity and m/z values of the chemicals that would be observed at this time, as they will not have previously been observed.…”

“…To validate simulated results, we generated a large real dataset in which the same sample, BeerQCB (introduced in Section 2.1) was fragmented using all combinations of N = (1,2,3,4,5,10,15,20,35,50) and DEW = (15,30,60,120). The minimum MS1 intensity threshold to fragment was completely disabled for this experiment to allow a consistent number of MS scans to be acquired under the different scenarios (see Section 2.1.3).…”

“…An appealing alternative way to evaluate fragmentation strategies is through the use of a simulator, which can replicate the underlying LC-MS/MS processes and allow researchers to prototype and compare strategies before validation on the actual MS instrument. Although some mass spectrometry simulators exist they are typically focused on proteomics and do not include simulation of the MS2 acquisition strategy within a chromatographic run [14,16,15,4,3,9]. Additionally existing simulators do not allow for real-time control of scan events (such as programmatically determining which m/z ranges to scan at a particular retention time), a crucial function for developing novel fragmentation strategies that can be controlled through libraries available with modern mass spectrometers, e.g.…”