Best practices and tools in R and Python for statistical processing and visualization of lipidomics and metabolomics data

Abstract Mass spectrometry-based lipidomics and metabolomics generate extensive data sets that, along with metadata such as clinical parameters, require specific data exploration skills to identify and visualize statistically significant trends and biologically relevant differences. Besides tailored...

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Bibliografiske detaljer

Principais autores:	Jakub Idkowiak, Jonas Dehairs, Jana Schwarzerová, Dominika Olešová, Jacob X. M. Truong, Aleš Kvasnička, Marios Eftychiou, Ruben Cools, Xander Spotbeen, Robert Jirásko, Vullnet Veseli, Marco Giampà, Vincent de Laat, Lisa M. Butler, Wolfram Weckwerth, David Friedecký, Jonas Demeulemeester, Karel Hron, Johannes V. Swinnen, Michal Holčapek
Format:	Artigo
Sprog:	Inglês
Udgivet:	Nature Portfolio 2025-09-01
Serier:	Nature Communications
Online adgang:	https://doi.org/10.1038/s41467-025-63751-1
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