ArticleIEEE transactions on visualization and computer graphics2018
HiPiler: Visual Exploration of Large Genome Interaction Matrices with Interactive Small Multiples.
Article in IEEE transactions on visualization and computer graphics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Aardvark: Composite Visualizations of Trees, Time-Series, and Images.IEEE transactions on visualization and computer graphics · 2025Article
- HiCognition: a visual exploration and hypothesis testing tool for 3D genomics.Genome biology · 2023Article
- DRAVA: Aligning Human Concepts with Machine Learning Latent Dimensions for the Visual Exploration of Small Multiples.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2023Article
- Identification of chromatin loops from Hi-C interaction matrices by CTCF-CTCF topology classification.NAR genomics and bioinformatics · 2022Article
- Visualizing and Annotating Hi-C Data.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Gosling: A Grammar-based Toolkit for Scalable and Interactive Genomics Data Visualization.IEEE transactions on visualization and computer graphics · 2022Article
- A Generic Framework and Library for Exploration of Small Multiples through Interactive Piling.IEEE transactions on visualization and computer graphics · 2021Article
- Cardioinformatics: the nexus of bioinformatics and precision cardiology.Briefings in bioinformatics · 2020Article
- Coolpup.py: versatile pile-up analysis of Hi-C data.Bioinformatics (Oxford, England) · 2020Article
- Pattern-Driven Navigation in 2D Multiscale Visualizations with Scalable Insets.IEEE transactions on visualization and computer graphics · 2020Article
- Genome-wide search of nucleosome patterns using visual analytics.Bioinformatics (Oxford, England) · 2019Article
- Tasks, Techniques, and Tools for Genomic Data Visualization.Computer graphics forum : journal of the European Association for Computer Graphics · 2019Article
- Visual Pattern-Driven Exploration of Big Data.2018 International Symposium on Big Data Visual and Immersive Analytics (BDVA) : Konstanz, Germany, October 17 -19, 2018. IEEE International Symposium on Big Data Visual and Immersive Analytics (4th : 2018 : Konstanz, Germany) · 2018Article
- HiGlass: web-based visual exploration and analysis of genome interaction maps.Genome biology · 2018Article
- Orientation-dependent Dxz4 contacts shape the 3D structure of the inactive X chromosome.Nature communications · 2018Article
- Challenges for visualizing three-dimensional data in genomic browsers.FEBS letters · 2017Review
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5 authors.
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Abstract
This paper presents an interactive visualization interface-HiPiler-for the exploration and visualization of regions-of-interest in large genome interaction matrices. Genome interaction matrices approximate the physical distance of pairs of regions on the genome to each other and can contain up to 3 million rows and columns with many sparse regions. Regions of interest (ROIs) can be defined, e.g., by sets of adjacent rows and columns, or by specific visual patterns in the matrix. However, traditional matrix aggregation or pan-and-zoom interfaces fail in supporting search, inspection, and comparison of ROIs in such large matrices. In HiPiler, ROIs are first-class objects, represented as thumbnail-like "snippets". Snippets can be interactively explored and grouped or laid out automatically in scatterplots, or through dimension reduction methods. Snippets are linked to the entire navigable genome interaction matrix through brushing and linking. The design of HiPiler is based on a series of semi-structured interviews with 10 domain experts involved in the analysis and interpretation of genome interaction matrices. We describe six exploration tasks that are crucial for analysis of interaction matrices and demonstrate how HiPiler supports these tasks. We report on a user study with a series of data exploration sessions with domain experts to assess the usability of HiPiler as well as to demonstrate respective findings in the data.
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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.