RT Journal Article
SR Electronic
T1 LipidMS 3.0: an R-package and a web-based tool for LC-MS/MS data processing and lipid annotation
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2022.02.25.476005
DO 10.1101/2022.02.25.476005
A1 María Isabel Alcoriza-Balaguer
A1 Juan Carlos García-Cañaveras
A1 Francisco Javier Ripoll-Esteve
A1 Agustín Lahoz
YR 2022
UL http://biorxiv.org/content/early/2022/02/28/2022.02.25.476005.abstract
AB Summary LipidMS was initially envisioned to use fragmentation rules and data-independent acquisition (DIA) for lipid annotation. However, data-dependent acquisition (DDA) remains the most widespread acquisition mode for untargeted LC-MS/MS-based lipidomics. Here we present LipidMS 3.0, an R package that not only adds DDA and new lipid classes to its pipeline, but also the required functionalities to cover the whole data analysis workflow from pre-processing (i.e., peak-peaking, alignment and grouping) to lipid annotation. We applied the new workflow in the analysis of a serum dataset acquired in MS, DDA and DIA modes. Our results show that LipidMS 3.0 data pre-processing outperforms XCMS and complements those lipids annotated using MS-DIAL, one of the most widely used tools in lipidomics. To extend and facilitate LipidMS 3.0 usage among less experienced R-programming users the workflow has been also implemented as a web-based application.Availability and Implementation LipidMS R-package is freely available at https://CRAN.R-project.org/package=LipidMS and as a website at http://www.lipidms.com.Competing Interest StatementThe authors have declared no competing interest.