State of the Field in Multi-Omics Research: From Computational Needs to Data Mining and Sharing

Multi-omics, variously called integrated omics, pan-omics, and trans-omics, aims to combine two or more omics data sets to aid in data analysis, visualization and interpretation to determine the mechanism of a biological process. Multi-omics efforts have taken center stage in biomedical research lea...

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Bibliographic Details
Published in:Frontiers in genetics Vol. 11; p. 610798
Main Authors: Krassowski, Michal, Das, Vivek, Sahu, Sangram K., Misra, Biswapriya B.
Format: Journal Article
Language:English
Published: Switzerland Frontiers Media S.A 10.12.2020
Subjects:
benchmarking
FAIR
Genetics
integrated omics
machine learning
multi-omics
reproducibility
visualization
FAIR
benchmarking
data heterogeneity
reproducibility
multi-omics
integrated omics
machine learning
ISSN:1664-8021, 1664-8021
Online Access:Get full text
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Summary:Multi-omics, variously called integrated omics, pan-omics, and trans-omics, aims to combine two or more omics data sets to aid in data analysis, visualization and interpretation to determine the mechanism of a biological process. Multi-omics efforts have taken center stage in biomedical research leading to the development of new insights into biological events and processes. However, the mushrooming of a myriad of tools, datasets, and approaches tends to inundate the literature and overwhelm researchers new to the field. The aims of this review are to provide an overview of the current state of the field, inform on available reliable resources, discuss the application of statistics and machine/deep learning in multi-omics analyses, discuss findable, accessible, interoperable, reusable (FAIR) research, and point to best practices in benchmarking. Thus, we provide guidance to interested users of the domain by addressing challenges of the underlying biology, giving an overview of the available toolset, addressing common pitfalls, and acknowledging current methods’ limitations. We conclude with practical advice and recommendations on software engineering and reproducibility practices to share a comprehensive awareness with new researchers in multi-omics for end-to-end workflow.
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ORCID: Michal Krassowski, orcid.org/0000-0002-9638-7785; Vivek Das, orcid.org/0000-0003-0614-0373; Sangram K. Sahu, orcid.org/0000-0001-5010-9539; Biswapriya B. Misra, orcid.org/0000-0003-2589-6539
Reviewed by: Heinz Himmelbauer, University of Natural Resources and Life Sciences, Vienna, Austria; Subina Mehta, University of Minnesota Twin Cities, United States; Wan M. Aizat, National University of Malaysia, Malaysia
Edited by: Fatemeh Maghuly, University of Natural Resources and Life Sciences, Vienna, Austria
This article was submitted to Systems Biology, a section of the journal Frontiers in Genetics
ISSN:1664-8021
1664-8021
DOI:10.3389/fgene.2020.610798