Integrating imaging and omics data: A review

We refer to omics imaging as an emerging interdisciplinary field concerned with the integration of data collected from biomedical images and omics analyses. Bringing together information coming from different sources, it permits to reveal hidden genotype–phenotype relationships, with the aim of better understanding the onset and progression of many diseases, and identifying new diagnostic and prognostic biomarkers. More in detail, biomedical images, generated by anatomical or functional techniques, are processed to extract hundreds of numerical features describing visual aspects – as in solid cancer imaging – or functional elements – as in neuroimaging. These imaging features are then complemented and integrated with genotypic and phenotypic information, such as DNA mutations, RNA expression levels, and protein abundances. Apart from the difficulties arising from imaging and omics analyses alone, the process of integrating, combining, processing, and making sense of the omics imaging data is quite challenging, owed to the heterogeneity of the sources, the high dimensionality of the resulting feature space, and the reduced availability of freely accessible, large, and well-curated datasets containing both images and omics data for each sample. In this review, we present the state of the art of omics imaging, with the aim of providing the interested reader a unique source of information, with links for further detailed information. Based on the existing literature, we describe both the omics and imaging data that have been adopted, provide a list of curated databases of integrated resources, discuss the types of adopted features, give hints on the used data analysis methods, and overview current research in this field.