Data integration through canonical correlation analysis and its application to OMICs research.

Autor: Wróbel S; Department of Medical Physics, Jagiellonian University, Marian Smoluchowski Institute of Physics, Krakow, Poland., Turek C; Department of Bioinformatics and Telemedicine, Jagiellonian University-Medical College, Krakow, Poland., Stępień E; Department of Medical Physics, Jagiellonian University, Marian Smoluchowski Institute of Physics, Krakow, Poland; Center for Theranostics, Jagiellonian University ul. Kopernika 40, 31-034 Kraków, Poland; Total-Body Jagiellonian-PET Laboratory, Jagiellonian University, Kraków, Poland. Electronic address: e.stepien@uj.edu.pl., Piwowar M; Department of Bioinformatics and Telemedicine, Jagiellonian University-Medical College, Krakow, Poland. Electronic address: mpiwowar@cm-uj.krakow.pl.
Jazyk: angličtina
Zdroj: Journal of biomedical informatics [J Biomed Inform] 2024 Mar; Vol. 151, pp. 104575. Date of Electronic Publication: 2023 Dec 10.
DOI: 10.1016/j.jbi.2023.104575
Abstrakt: The subject of the paper is a review of multidimensional data analysis methods, which is the canonical analysis with its various variants and its use in omics data research. The dynamic development of high-throughput methods, and with them the availability of large and constantly growing data resources, forces the development of new analytical approaches that allow the review of the analyzed processes, taking into account data from various levels of the organization of living organisms. The multidimensional perspective allows for the assessment of the analyzed phenomenon in a more realistic way, as it generally takes into account much more data (including OMICs data). Without omitting the complexity of an organism, the method simplifies the multidimensional view, finally giving the result so that the researcher can draw practical conclusions. This is particularly important in medical sciences, where the study of pathological processes is usually aimed at developing treatment regimens. One of the primary methods for studying biomedical processes in a multidimensional approach is the canonical correlation analysis (CCA) with various variants. The use of CCA unique methodologies for simultaneous analysis of multiset biomolecular data opens up new avenues for studying previously undiscovered processes and interdependencies such as e.g. in the tumor microenvironment (TME) connected to intercellular communication. Because of the huge and still untapped potential of canonical correlation, in this review available implementations of CCA techniques are presented. In particular, the possibility of using the technique of canonical correlation analysis for OMICs data is emphasized.
Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Monika Piwowar reports article publishing charges was provided by Jagiellonian University in Kraków Medical College.
(Copyright © 2023 Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
Externí odkaz: