MobilityTransformR: an R package for effective mobility transformation of CE-MS data-Reference-Cited by-同舟云学术

MobilityTransformR: an R package for effective mobility transformation of CE-MS data

Published:2022-07-04 Issue:16 Volume:38 Page:4044-4045
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Salzer Liesa¹^ORCID,Witting Michael²³^ORCID,Schmitt-Kopplin Philippe¹²

Affiliation:

1. Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München , D-85764 Neuherberg, Germany

2. Chair of Analytical Food Chemistry, TUM School of Life Sciences, Technical University of Munich , D-85354 Freising, Germany

3. Metabolomics and Proteomics Core, Helmholtz Zentrum München , D-85764 Neuherberg, Germany

Abstract

Abstract Summary We present MobilityTransformR, an R/Bioconductor package for the effective mobility scaling of capillary zone electrophoresis-mass spectrometry (CE-MS) data. It uses functionality from different R packages that are frequently used for data processing and analysis in MS-based metabolomics workflows, allowing the subsequent use of reproducible transformed CE-MS data in existing workflows. Availability and implementation MobilityTransformR is implemented in R (Version >= 4.2) and can be downloaded directly from the Bioconductor database (https://bioconductor.org/packages/MobilityTransformR) or GitHub (https://github.com/LiesaSalzer/MobilityTransformR). Supplementary information Supplementary data are available at Bioinformatics online.

Funder

Deutsche Forschungsgemeinschaft

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btac441/44886790/btac441.pdf

Reference11 articles.

1. A mature ROMANCE: a matter of quantity and how two can be better than one;Codesido;ChemRxiv,2020

2. New insights into the conversion of electropherograms to the effective electrophoretic mobility scale;Codesido;Electrophoresis,2021

3. Development of a capillary electrophoretic method for the analysis of low-molecular-weight amines from metal working fluid aerosols and ambient air;Fekete;Electrophoresis,2006

4. MSnbase: efficient and elegant R-Based processing and visualization of raw mass spectrometry data;Gatto;J. Proteome Res,2021

5. ROMANCE: a new software tool to improve data robustness and feature identification in CE-MS metabolomics;González-Ruiz;Electrophoresis,2018

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