Computational Analysis of Phosphoproteomics Data in Multi‐Omics Cancer Studies

Multiple types of molecular data for the same set of clinical samples are increasingly available and may be analyzed jointly in an integrative analysis to maximize comprehensive biological insight. This analysis is important as separate analyses of individual omics data types usually do not fully ex...

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Veröffentlicht in:Proteomics (Weinheim) 2021-02, Vol.21 (3-4), p.e1900312-n/a
Hauptverfasser: Mantini, Giulia, Pham, Thang V., Piersma, Sander R., Jimenez, Connie R.
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container_issue 3-4
container_start_page e1900312
container_title Proteomics (Weinheim)
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creator Mantini, Giulia
Pham, Thang V.
Piersma, Sander R.
Jimenez, Connie R.
description Multiple types of molecular data for the same set of clinical samples are increasingly available and may be analyzed jointly in an integrative analysis to maximize comprehensive biological insight. This analysis is important as separate analyses of individual omics data types usually do not fully explain disease phenotypes. An increasing number of studies have now been focusing on multi‐omics data integration, yet not many studies have included phosphoproteomics data, an important layer for understanding signaling pathways. Multi‐omics integration methods with phosphoproteomics data are reviewed in the context of cancer research as well as multi‐omics methods papers that would be promising to apply to phosphoproteomics data. Analysis of individual data types is still the major approach even in large cohort proteogenomics studies. Hence, a section is dedicated on possible integrative methods for multi‐omics and phosphoproteomics data. In summary, this review provides the readers with both currently used integrative methods previously applied to phosphoproteomics and multi‐omics data integration and other algorithms for multi‐omics data integration promising for future application to phosphoproteomics data.
doi_str_mv 10.1002/pmic.201900312
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source Wiley Online Library Journals Frontfile Complete
subjects Algorithms
bioinformatics
Cancer
Computer applications
Data analysis
Data integration
Integration
multi‐omics
Phenotypes
phosphoproteomics
title Computational Analysis of Phosphoproteomics Data in Multi‐Omics Cancer Studies
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