Review
Version 1
Preserved in Portico This version is not peer-reviewed
Approaches to Integrating Metabolomics and Multi-Omics Data: A Primer
Version 1
: Received: 23 January 2021 / Approved: 25 January 2021 / Online: 25 January 2021 (16:19:31 CET)
A peer-reviewed article of this Preprint also exists.
Jendoubi, T. Approaches to Integrating Metabolomics and Multi-Omics Data: A Primer. Metabolites 2021, 11, 184. Jendoubi, T. Approaches to Integrating Metabolomics and Multi-Omics Data: A Primer. Metabolites 2021, 11, 184.
Abstract
Metabolomics deals with multiple and complex chemical reactions within living organisms and how these are influenced by external or internal perturbations. It lies at the heart of omics profiling technologies not only as the underlying biochemical layer that reflects information expressed by the genome, the transcriptome and the proteome, but also as the closest layer to the phenome. The combination of metabolomics data with the information available from genomics, transcriptomics, and proteomics offers unprecedented possibilities to enhance current understanding of biological functions, elucidate their underlying mechanisms and uncover hidden associations between omics variables. As a result, a vast array of computational tools have been developed to assist with integrative analysis of metabolomics data with different omics. Here, we review and propose five criteria – hypothesis, data types, strategies, study design and study focus – to classify statistical multi-omics data integration approaches into state-of-the-art classes under which all existing statistical methods fall. The purpose of this review is to look at various aspects that lead the choice of the statistical integrative analysis pipeline in terms of the different classes. We will draw a particular attention to metabolomics and genomics data to assist those new to this field in the choice of the integrative analysis pipeline.
Keywords
Data integration; multi-omics; integration strategies; genomics
Subject
Biology and Life Sciences, Biochemistry and Molecular Biology
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Comments (0)
We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.
Leave a public commentSend a private comment to the author(s)
* All users must log in before leaving a comment
