Novel multivariate methods for integration of genomics and proteomics data: applications in a kidney transplant rejection study

Guenther, Oliver P., Shin, Heesun, Ng, Raymond T., McMaster, W. Robert, McManus, Bruce M., Keown, Paul A., Tebbutt, Scott. J. and Le Cao, Kim-Anh (2014) Novel multivariate methods for integration of genomics and proteomics data: applications in a kidney transplant rejection study. OMICS A Journal of Integrative Biology, 18 11: 682-695. doi:10.1089/omi.2014.0062


Author Guenther, Oliver P.
Shin, Heesun
Ng, Raymond T.
McMaster, W. Robert
McManus, Bruce M.
Keown, Paul A.
Tebbutt, Scott. J.
Le Cao, Kim-Anh
Title Novel multivariate methods for integration of genomics and proteomics data: applications in a kidney transplant rejection study
Journal name OMICS A Journal of Integrative Biology   Check publisher's open access policy
ISSN 1557-8100
1536-2310
Publication date 2014-11-01
Sub-type Article (original research)
DOI 10.1089/omi.2014.0062
Open Access Status
Volume 18
Issue 11
Start page 682
End page 695
Total pages 14
Place of publication New Rochelle, NY, United States
Publisher Mary Ann Liebert Inc.
Collection year 2015
Language eng
Abstract Multi-omics research is a key ingredient of data-intensive life sciences research, permitting measurement of biological molecules at different functional levels in the same individual. For a complete picture at the biological systems level, appropriate statistical techniques must however be developed to integrate different 'omics' data sets (e.g., genomics and proteomics). We report here multivariate projection-based analyses approaches to genomics and proteomics data sets, using the case study of and applications to observations in kidney transplant patients who experienced an acute rejection event (n=20) versus non-rejecting controls (n=20). In this data sets, we show how these novel methodologies might serve as promising tools for dimension reduction and selection of relevant features for different analytical frameworks. Unsupervised analyses highlighted the importance of post transplant time-of-rejection, while supervised analyses identified gene and protein signatures that together predicted rejection status with little time effect. The selected genes are part of biological pathways that are representative of immune responses. Gene enrichment profiles revealed increases in innate immune responses and neutrophil activities and a depletion of T lymphocyte related processes in rejection samples as compared to controls. In all, this article offers candidate biomarkers for future detection and monitoring of acute kidney transplant rejection, as well as ways forward for methodological advances to better harness multi-omics data sets.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
Institute for Molecular Bioscience - Publications
UQ Diamantina Institute Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 10 times in Thomson Reuters Web of Science Article | Citations
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