Dataset and R Code used in the manuscript 'Plasma and Platelet Lipidome Changes in Fabry Disease'

SUMMARY This repository contains mass-spectrometry (MS) raw data files and R scripts used in the manuscript “Plasma and Platelet Lipidome Changes in Fabry Disease” by Bo Burla, Jeongah Oh, Albina Nowak, Nathalie Piraud, Eduardo Meyer, Ding Mei, Anne K Bendt, Jan-Dirk Studt, Beat M Frey, Federico Torta, Markus R Wenk, and Pierre-Alexandre Krayenbuhl, DATA STRUCTURE (1) Mass-spectrometry raw data files in "FabryLipidomics_Burla2024_RawDataMS_V5.zip": This zip file contains folders for each measured lipid panel comprising of LC-MS-MRM (Agilent QQQ MS) raw data. Each raw data subfolder (.d) in these folders corresponds to the raw data of one analysis/sample. The subfolders “QuantResults” contain Agilent MassHunter Quant batch files (*.batch.bin) used for the peak picking and peak integration of the corresponding panel. (2) RStudio project in "GITHUB_Burla_2024_FabryLipidomics-1.0.zip" (downloaded from GitHub) containing pre-processed raw data (i.e peak areas and other information from peak integration), experimental metadata, and the R code/pipeline used to postprocess, analyze and visualize the data for the manuscript VIEWING THE DATA - Raw data files (.d) can be viewed and analysed using Agilent software (Agilent MassHunter QUAL or MassHunter QUANT) - Raw data files (.d) can also be converted to the open *.mzML format using msconvert (https://proteowizard.sourceforge.io/tools/msconvert.html) and then viewed in e.g. Skyline (https://skyline.ms) or other open-source tools and R/Python scripts supporting this format. - The MassHunter QUANT batch file (*.batch.bin) containing the peak picking and integration definitions can only be viewed using Agilent MassHunter QUANT (version 10 or higher) - The pre-processed data (peak areas) and corresponding experimental metadata are within the folder "data" of the RStudio project folder (GITHUB_Burla_2024_FabryLipidomics-1.0.zip) - The R data analysis scripts can be opened in R/RStudio. For further information please refer to README.html within this RStudio project. CONTACT Bo Johannes Burla, PhD, Singapore Lipidomics Incubator, National University of Singapore, [e-mail]