Visualization Challenges of Variant Interpretation in Multiscale NGS Data

dc.contributor.authorStåhlbom, Emiliaen_US
dc.contributor.authorMolin, Jesperen_US
dc.contributor.authorLundström, Claesen_US
dc.contributor.authorYnnerman, Andersen_US
dc.contributor.editorKrone, Michaelen_US
dc.contributor.editorLenti, Simoneen_US
dc.contributor.editorSchmidt, Johannaen_US
dc.date.accessioned2022-06-02T15:29:18Z
dc.date.available2022-06-02T15:29:18Z
dc.date.issued2022
dc.description.abstractThere 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.en_US
dc.description.sectionheadersPosters
dc.description.seriesinformationEuroVis 2022 - Posters
dc.identifier.doi10.2312/evp.20221132
dc.identifier.isbn978-3-03868-185-4
dc.identifier.pages107-109
dc.identifier.pages3 pages
dc.identifier.urihttps://doi.org/10.2312/evp.20221132
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/evp20221132
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Human-centered computing --> Information visualization; Visualization design and evaluation methods; Applied computing --> Genomics
dc.subjectHuman centered computing
dc.subjectInformation visualization
dc.subjectVisualization design and evaluation methods
dc.subjectApplied computing
dc.subjectGenomics
dc.titleVisualization Challenges of Variant Interpretation in Multiscale NGS Dataen_US
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