Multi-omics Analysis

Multi-omics analysis is a biological research approach which brings together multiple ‘omics data types, such as genomics, proteomics, transcriptomics, metabolomics and others. By layering these data together, researchers are able to study life in concerted ways and glean complex biological insights that might be undetectable using a single method. Combining multiple ‘omics data sources provides opportunities to discover novel associations between biological entities, pinpoint relevant biomarkers and build elaborate markers of disease and physiology.

Join the conversation - all welcome!

We are providing a focal point for Australian life science researchers and bioinformaticians who are undertaking multi-omics analysis to voice their infrastructure requirements and challenges, and to inform what computational infrastructure or services are needed to better support multi-omics analysis within Australia, and globally.

During 2024 we will be drafting a “Multi-omics Infrastructure Roadmap for Australia” which will present a vision for shared national infrastructure that will help researchers undertake multi-omics analysis.

Header image: Sample prediction area plots from a PLS-DA model applied on a microarray data set with the expression levels of 2,308 genes on 63 samples. Reproduced under CC-BY 4.0 licence from Rohart F, Gautier B, Singh A, Lê Cao KA (2017) mixOmics: An R package for ‘omics feature selection and multiple data integration. PLOS Computational Biology 13(11): e1005752