Ståhlbom, EmiliaMolin, JesperLundström, ClaesYnnerman, AndersKrone, MichaelLenti, SimoneSchmidt, Johanna2022-06-022022-06-022022978-3-03868-185-4https://doi.org/10.2312/evp.20221132https://diglib.eg.org:443/handle/10.2312/evp20221132There is currently a movement in health care towards precision medicine, where genomics often is the central diagnostic component for tailoring the treatment to the individual patient. We here present results from a domain characterization effort to pinpoint problems and possibilities for visualization of genomics data in the clinical workflow, with analysis of copy number variants as an example task. Five distinct characteristics have been identified. Clinical genomics data is inherently multiscale, riddled with artifacts and uncertainty, and many findings have unknown significance, so it is a challenging visual analytics domain. Moreover, as in other clinical domains, high efficiency is key. This characterization will form the basis for follow-on visualization prototyping.Attribution 4.0 International LicenseCCS Concepts: Human-centered computing --> Information visualization; Visualization design and evaluation methods; Applied computing --> GenomicsHuman centered computingInformation visualizationVisualization design and evaluation methodsApplied computingGenomics10.2312/evp.20221132107-1093 pages