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Calculation of QC metrics from mass spectrometry data


Data quality assessment is an integral part of preparatory data analysis to ensure sound biological information retrieval.

We present here the MsQuality package, which provides functionality to calculate quality metrics for mass spectrometry-derived, spectral data at the per-sample level. MsQuality relies on the mzQC framework of quality metrics defined by the Human Proteome Organization-Proteomics Standards Intitiative (HUPO-PSI). These metrics quantify the quality of spectral raw files using a controlled vocabulary.

The package is especially addressed towards users that acquire mass spectrometry data on a clinical/large scale: while it is easier to control for high-quality data acquisition in small-scale experiments, typically run in one or few batches, clinical data sets are often acquired over longer time frames and are prone to higher technical variation that is often unnoticed. MsQuality tries to address this problem by calculating metrics that can be stored along the spectral data sets (raw files or feature-extracted data sets). MsQuality, thus, facilitates the tracking of shifts in data quality and quantifies the quality using multiple metrics. It should be thus easier to identify samples that are of low quality (high-number of missing values, termination of chromatographic runs, low instrument sensitivity, etc.).

The MsQuality package allows to calculate low-level quality metrics that require minimum information on mass spectrometry data: retention time, m/z values, and associated intensities. The list included in the mzQC framework is excessive, also including metrics that rely on more high-level information, that might not be readily accessible from .raw or .mzML files, e.g. pump pressure mean, or rely on alignment results, e.g. retention time mean shift, signal-to-noise ratio, precursor errors (ppm).

The MsQuality package is built upon the Spectra and the MsExperiment package. Metrics will be calculated based on the information stored in a Spectra object, thus, the spectral data of each sample should be stored in one Spectra object. The MsExperiment serves as a container to store the mass spectral data of multiple samples. MsQuality enables the user to calculate quality metrics both on Spectra and MsExperiment objects.


You are welcome to


To install MsQuality, you have first to install the devtools package:


Install the MsQuality package then via


tnaake/MsQuality documentation built on Jan. 14, 2022, 7:34 p.m.