2024-03-28T11:19:09Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/1680782020-05-29T09:44:01Zcom_10261_5062com_10261_5col_10261_5064
http://hdl.handle.net/10261/168078
10.1002/pmic.201700327
347786
Chemometric Strategies for Peak Detection and Profiling from Multidimensional Chromatography
Wiley-Blackwell
2018
artículo
Navarro-Reig, Meritxell
Bedia, Carmen
Tauler, Romà
Jaumot, Joaquim
rp13644
Chemometrics
Comprehensive chromatography
Multidimensional chromatography
Peak detection
Peak resolution
2018
The increasing complexity of omics research has encouraged the development of new instrumental technologies able to deal with these challenging samples. In this way, the rise of multidimensional separations should be highlighted due to the massive amounts of information that provide with an enhanced analyte determination. Both proteomics and metabolomics benefit from this higher separation capacity achieved when different chromatographic dimensions are combined, either in LC or GC. However, this vast quantity of experimental information requires the application of chemometric data analysis strategies to retrieve this hidden knowledge, especially in the case of nontargeted studies. In this work, the most common chemometric tools and approaches for the analysis of this multidimensional chromatographic data are reviewed. First, different options for data preprocessing and enhancement of the instrumental signal are introduced. Next, the most used chemometric methods for the detection of chromatographic peaks and the resolution of chromatographic and spectral contributions (profiling) are presented. The description of these data analysis approaches is complemented with enlightening examples from omics fields that demonstrate the exceptional potential of the combination of multidimensional separation techniques and chemometric tools of data analysis. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
European Commission
Proteomics
2018