期刊
BMC SYSTEMS BIOLOGY
卷 12, 期 -, 页码 -出版社
BMC
DOI: 10.1186/s12918-018-0556-z
关键词
Molecular signatures; Omics data; Stratification; Systems medicine
资金
- Innovative Medicines Initiative U-BIOPRED project [115010]
- Innovative Medicines Initiative eTRIKS project [115446]
- BBSRC [BB/M012387/1] Funding Source: UKRI
Background: Multilevel data integration is becoming a major area of research in systems biology. Within this area, multi-'omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-'omics signatures of disease states. Methods: The framework is divided into four major steps: dataset subsetting, feature filtering, 'omics-based clustering and biomarker identification. Results: We illustrate the usefulness of this framework by identifying potential patient clusters based on integrated multi-'omics signatures in a publicly available ovarian cystadenocarcinoma dataset. The analysis generated a higher number of stable and clinically relevant clusters than previously reported, and enabled the generation of predictive models of patient outcomes. Conclusions: This framework will help health researchers plan and perform multi-'omics big data analyses to generate hypotheses and make sense of their rich, diverse and ever growing datasets, to enable implementation of translational P4 medicine.
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