“Notame”: Workflow for non-targeted LC-MS metabolic profiling
Artikel i vetenskaplig tidskrift, 2020
Metabolomics analysis generates vast arrays of data, necessitating comprehensive workflows involving expertise in analytics, biochemistry and bioinformatics in order to provide coherent and high-quality data that enable discovery of robust and biologically significant metabolic findings. In this protocol article, we introduce notame, an analytical workflow for non-targeted metabolic profiling approaches, utilizing liquid chromatography-mass spectrometry analysis. We provide an overview of lab protocols and statistical methods that we commonly practice for the analysis of nutritional metabolomics data. The paper is divided into three main sections: the first and second sections introducing the background and the study designs available for metabolomics research and the third section describing in detail the steps of the main methods and protocols used to produce, preprocess and statistically analyze metabolomics data and, finally, to identify and interpret the compounds that have emerged as interesting.
Metabolomics
Computational statistical
Supervised learning
Unsupervised learning
Metabolic profiling
LC-MS
Pathway analysis
Mass spectrometry
Författare
Anton Klåvus
Itä-Suomen Yliopisto
Marietta Kokla
Itä-Suomen Yliopisto
Stefania Noerman
Itä-Suomen Yliopisto
Ville Mikael Koistinen
Itä-Suomen Yliopisto
Marjo Tuomainen
Itä-Suomen Yliopisto
Iman Zarei
Itä-Suomen Yliopisto
Topi Meuronen
Itä-Suomen Yliopisto
Merja R. Häkkinen
Itä-Suomen Yliopisto
Soile Rummukainen
Itä-Suomen Yliopisto
Ambrin Farizah Babu
Itä-Suomen Yliopisto
Taisa Sallinen
Itä-Suomen Yliopisto
Olli Kärkkäinen
Itä-Suomen Yliopisto
Jussi Paananen
Itä-Suomen Yliopisto
David Broadhurst
Edith Cowan University
Carl Brunius
Chalmers, Biologi och bioteknik, Livsmedelsvetenskap
Kati Hanhineva
Chalmers, Biologi och bioteknik, Livsmedelsvetenskap
Turun Yliopisto
Itä-Suomen Yliopisto
Metabolites
2218-1989 (ISSN) 22181989 (eISSN)
Vol. 10 4 135Ämneskategorier
Cell- och molekylärbiologi
DOI
10.3390/metabo10040135