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STATegra: Multi-Omics Data Integration - A Conceptual Scheme With a Bioinformatics Pipeline.

Authors :
Planell N
Lagani V
Sebastian-Leon P
van der Kloet F
Ewing E
Karathanasis N
Urdangarin A
Arozarena I
Jagodic M
Tsamardinos I
Tarazona S
Conesa A
Tegner J
Gomez-Cabrero D
Source :
Frontiers in genetics [Front Genet] 2021 Mar 04; Vol. 12, pp. 620453. Date of Electronic Publication: 2021 Mar 04 (Print Publication: 2021).
Publication Year :
2021

Abstract

Technologies for profiling samples using different omics platforms have been at the forefront since the human genome project. Large-scale multi-omics data hold the promise of deciphering different regulatory layers. Yet, while there is a myriad of bioinformatics tools, each multi-omics analysis appears to start from scratch with an arbitrary decision over which tools to use and how to combine them. Therefore, it is an unmet need to conceptualize how to integrate such data and implement and validate pipelines in different cases. We have designed a conceptual framework (STATegra), aiming it to be as generic as possible for multi-omics analysis, combining available multi-omic anlaysis tools (machine learning component analysis, non-parametric data combination, and a multi-omics exploratory analysis) in a step-wise manner. While in several studies, we have previously combined those integrative tools, here, we provide a systematic description of the STATegra framework and its validation using two The Cancer Genome Atlas (TCGA) case studies. For both, the Glioblastoma and the Skin Cutaneous Melanoma (SKCM) cases, we demonstrate an enhanced capacity of the framework (and beyond the individual tools) to identify features and pathways compared to single-omics analysis. Such an integrative multi-omics analysis framework for identifying features and components facilitates the discovery of new biology. Finally, we provide several options for applying the STATegra framework when parametric assumptions are fulfilled and for the case when not all the samples are profiled for all omics. The STATegra framework is built using several tools, which are being integrated step-by-step as OpenSource in the STATeg R a Bioconductor package.<br />Competing Interests: VL and IT were employed by Gnosis Data Analysis P.C., Greece. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.<br /> (Copyright © 2021 Planell, Lagani, Sebastian-Leon, van der Kloet, Ewing, Karathanasis, Urdangarin, Arozarena, Jagodic, Tsamardinos, Tarazona, Conesa, Tegner and Gomez-Cabrero.)

Details

Language :
English
ISSN :
1664-8021
Volume :
12
Database :
MEDLINE
Journal :
Frontiers in genetics
Publication Type :
Academic Journal
Accession number :
33747045
Full Text :
https://doi.org/10.3389/fgene.2021.620453