visMOP - A Visual Analytics Approach for Multi-omics Pathways

Abstract
We present an approach for the visual analysis of multi-omics data obtained using high-throughput methods. The term ''omics'' denotes measurements of different types of biologically relevant molecules, like the products of gene transcription (transcriptomics) or the abundance of proteins (proteomics). Current popular visualization approaches often only support analyzing each of these omics separately. This, however, disregards the interconnectedness of different biologically relevant molecules and processes. Consequently, it describes the actual events in the organism suboptimally or only partially. Our visual analytics approach for multi-omics data provides a comprehensive overview and details-on-demand by integrating the different omics types in multiple linked views. To give an overview, we map the measurements to known biological pathways and use a combination of a clustered network visualization, glyphs, and interactive filtering. To ensure the effectiveness and utility of our approach, we designed it in close collaboration with domain experts and assessed it using an exemplary workflow with real-world transcriptomics, proteomics, and lipidomics measurements from mice.
Description

CCS Concepts: Human-centered computing -> Graph drawings; Visualization techniques; Applied computing -> Bioinformatics

        
@article{
10.1111:cgf.14828
, journal = {Computer Graphics Forum}, title = {{
visMOP - A Visual Analytics Approach for Multi-omics Pathways
}}, author = {
Brich, Nicolas
and
Schacherer, Nadine
and
Hoene, Miriam
and
Weigert, Cora
and
Lehmann, Rainer
and
Krone, Michael
}, year = {
2023
}, publisher = {
The Eurographics Association and John Wiley & Sons Ltd.
}, ISSN = {
1467-8659
}, DOI = {
10.1111/cgf.14828
} }
Citation
Collections