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 large scale (e.g. data sets from clinical settings
consisting of several thousands of samples): 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
MsQuality
is available via Bioconductor. To install the package, users can
either install from the
devel branch
or from the current
RELEASE branch.
To install MsQuality
, you have first to install the
BiocManager
and
remotes
package:
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
if (!requireNamespace("remotes", quietly = TRUE))
install.packages("remotes")
Install the MsQuality
package then via
## to install from Bioconductor
BiocManager::install("MsQuality")
## to install the development version from GitHub
BiocManager::install("tnaake/MsQuality")
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