ArticleBioinformatics (Oxford, England)2020
Proactive visual and statistical analysis of genomic data in Epiviz.
Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Gosling: A Grammar-based Toolkit for Scalable and Interactive Genomics Data Visualization.IEEE transactions on visualization and computer graphics · 2022Article
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Authors and funding
5 authors.
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Abstract
motivationIntegrative analysis of genomic data that includes statistical methods in combination with visual exploration has gained widespread adoption. Many existing methods involve a combination of tools and resources: user interfaces that provide visualization of large genomic datasets, and computational environments that focus on data analyses over various subsets of a given dataset. Over the last few years, we have developed Epiviz as an integrative and interactive genomic data analysis tool that incorporates visualization tightly with state-of-the-art statistical analysis framework.
resultsIn this article, we present Epiviz Feed, a proactive and automatic visual analytics system integrated with Epiviz that alleviates the burden of manually executing data analysis required to test biologically meaningful hypotheses. Results of interest that are proactively identified by server-side computations are listed as notifications in a feed. The feed turns genomic data analysis into a collaborative work between the analyst and the computational environment, which shortens the analysis time and allows the analyst to explore results efficiently. We discuss three ways where the proposed system advances the field of genomic data analysis: (i) takes the first step of proactive data analysis by utilizing available CPU power from the server to automate the analysis process; (ii) summarizes hypothesis test results in a way that analysts can easily understand and investigate; (iii) enables filtering and grouping of analysis results for quick search. This effort provides initial work on systems that substantially expand how computational and visualization frameworks can be tightly integrated to facilitate interactive genomic data analysis. AVAILABILITY AND IMPLEMENTATION: The source code for Epiviz Feed application is available at http://github.com/epiviz/epiviz_feed_polymer. The Epiviz Computational Server is available at http://github.com/epiviz/epiviz-feed-computation. Please refer to Epiviz documentation site for details: http://epiviz.github.io/.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.