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This is the development version of MsQuality; for the stable release version, see MsQuality.

MsQuality - Quality metric calculation from Spectra and MsExperiment objects

Bioconductor version: Development (3.19)

The MsQuality 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 Proteom Organization-Proteomics Standards Initiative (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 large scale (e.g. data sets from clinical settings consisting of several thousands of samples). 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. MsQuality relies on the Spectra package, or alternatively the MsExperiment package, and its infrastructure to store spectral data.

Author: Thomas Naake [aut, cre] , Johannes Rainer [aut]

Maintainer: Thomas Naake <thomasnaake at>

Citation (from within R, enter citation("MsQuality")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


Reference Manual PDF


biocViews MassSpectrometry, Metabolomics, Proteomics, QualityControl, Software
Version 1.3.2
In Bioconductor since BioC 3.17 (R-4.3) (1 year)
License GPL-3
Depends R (>= 4.2.0)
Imports BiocParallel(>= 1.32.0), ggplot2 (>= 3.3.5), htmlwidgets (>= 1.5.3), methods (>= 4.2.0), msdata(>= 0.32.0), MsExperiment(>= 0.99.0), plotly (>=, ProtGenerics(>= 1.24.0), rlang (>= 1.1.1), rmzqc (>= 0.5.0), shiny (>= 1.6.0), shinydashboard (>= 0.7.1), Spectra(>= 1.13.2), stats (>= 4.2.0), stringr (>= 1.4.0), tibble (>= 3.1.4), tidyr (>= 1.1.3), utils (>= 4.2.0)
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Suggests BiocGenerics(>= 0.24.0), BiocStyle(>= 2.6.1), dplyr (>= 1.0.5), knitr (>= 1.11), mzR(>= 2.32.0), rmarkdown (>= 2.7), S4Vectors(>= 0.29.17), testthat (>= 2.2.1)
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