In tnaake/MsQualityUtils: What the package does (short line)

BiocStyle::markdown()

library("knitr")
opts_chunk$set(stop_on_error = 1L)

Introduction {#sec-intro}

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

We present here the MsQualityUtils package, which provides functionality to create MsExperiment objects from mzML and MetIDQ-derived files. The MsExperiment files can subsequently be used to calculate quality metrics at the per-sample level using the MsQuality package.

MsQuality relies on the mzQC framework of quality metrics defined by the Human Proteome Organization-Proteomics Standards Intitiative (HUPO-PSI).

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. The MsQualityUtils package provides functionality to create MsExperiment objects that store the (spectral) information of mzML or MetIDQ files.

In this vignette, we will (i) create an MsExperiment object from MetIDQ-derived mass spectrometry data
and (ii) create an MsExperiment object from mzML mass spectrometry data.

Installation

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

install.packages("devtools")
library("devtools")

Install the MsQualityUtils package then via

install_github("tnaake/MsQualityUtils")

This will install this package and all eventually missing dependencies.

Questions and bugs {-}

MsQualityUtils is currently under active development. If you discover any bugs, typos or develop ideas of improving MsQuality feel free to raise an issue via GitHub or send a mail to the developer.

Prepare the environment

Load the MsQualityUtils package.

library("MsQualityUtils")

Create MsExperiment from MetIDQ files

MetIDQ$^{\mathrm{TM}}$ xlsx files are created by the Biocrates MetIDQ$^{\mathrm{TM}}$. They store information on metabolite concentration in their cells. The MsQualityUtils package provides functionality to retrieve the information stored in the MetIDQ$^{\mathrm{TM}}$ xlsx files and create Spectra objects from this. Typically, some of the measured metabolites are separated by liquid chromatography. We can pass a SummarizedExperiment object rt to the function ` that stores retention time values in theassayslot. If there is no objectrtpassed to the function, an internalrt` object will be used and retention times are taken therefrom.

First, we will create a list of Spectra objects. The list has two entries:

• the first entry contains all features found in the xlsx files (irrespective of their retentiont time),
• the second entry contains the features that are separated by a chromatographic method, these features have information on retention time values.

The function will create Spectra objects from all MetIDQ files that are found in path (createListOfSpectra will combine all MetIDQ files found in path).

The example file loaded is ac9b02908_si_002 from the publication by @Thompson2019. The xlsx file was only slightly modified to be able to be loaded by the biocrates function from the MatrixQCvis package.

path <- system.file("metidq", package = "MsQualityUtils")
sps_l <- createListOfSpectra(type = "MetIDQ", path = path, sheet = 1)

In a next step, we create a list of MsExperiment objects from the list of Spectra objects. The first entry of the list contains the MsExperiment object of features irrespective of their retention time. The second entry contains the MsExperiment object of features that are separated by a chromatographic method, these features have information on retention time values.

msexp_metidq_l <- createListOfMsExperimentFromListOfSpectra(sps_l = sps_l)

Create MsExperiment from mzML files

Here, we load the example files from the sciex data set of the msdata package and create a list of one Spectra object from the two provided mzML files. The function will create a Spectra object containing all mzML files that are found in the specified path.

path <- system.file("sciex", package = "msdata")
sps_l <- createListOfSpectra(type = "mzML", path = path)

In a next step, we calculate a list of one MsExperiment object from the list of Spectra objects:

msexp_mzml_l <- createListOfMsExperimentFromListOfSpectra(sps_l = sps_l)

Calculating the quality metrics on MsExperiment objects using MsQuality

The objects from the MsQualityUtils functions can directly be used by the MsQuality package.

The function calculateMetrics will iterate over the samples (referring to rows in sampleData(msexp))) and calculate the quality metrics on the corresponding Spectra objects.

library("MsQuality")
msexp_mzml <- msexp_mzml_l[[1]]
metrics_msexp <- calculateMetrics(object = msexp_mzml,
    metrics = qualityMetrics(msexp_mzml),
    relativeTo = "Q1", msLevel = 1L)
metrics_msexp

When passing an MsExperiment object to calculateMetrics a data.frame object is returned with the samples (derived from the rownames of sampleData(msexp)) in the rows and the metrics in columns.

We will show here the objects metrics_rplc_msexp and metrics_hilic_msexp

print("metrics_msexp")
rmarkdown::paged_table(as.data.frame(metrics_msexp))

Appendix {-}

Session information {-}

All software and respective versions to build this vignette are listed here:

sessionInfo()

References

tnaake/MsQualityUtils documentation built on Feb. 3, 2023, 6:32 a.m.