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User:TimAngus/sandbox/Graphia (software)

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Graphia
Developer(s)Graphia Technologies Limited
Initial release1 March 2019; 6 years ago (2019-03-01)[1]
Stable release
2.2 / 27 January 2021; 4 years ago (2021-01-27)[2]
Written inC++, OpenGL, Qt (software)
Operating systemWindows, macOS, Linux
Available inEnglish
TypeVisualization
LicenseGNU General Public License
Websitegraphia.app

Graphia is an open source data visualization software package that uses graph drawing for the interpretation of large and complex datasets.

History

Created by researchers hailing from the Roslin Institute, Graphia was developed by a company spun out from the University of Edinburgh. Unable to make a commercial success of it, the company folded in 2020 and the software was subsequently released [3] under an open source license.

Usage

Graphia was originally designed to create and visualize correlation graphs from the primary data that is produced in the life sciences. In this sense it may be considered a bioinformatics tool, indeed this is is primary use case[4][5][6][7]. Nevertheless, Graphia is data type agnostic and has also been used in other fields such as Genealogy and Social network analysis. Architecturally, a plugin system is used, meaning that Graphia can be extended beyond what is available by default.

Functionality

Graphia has a focus on interactivity, with its layout process occurring in real time and graph construction parameters adjustable on the fly. The latter is realised through a parametric style transformation system whereby individual processes which permute the graph are chained together, the results of which are immediately visible to the user. This approach reduces the round trip time that might be experienced compared to a process where the graph is repeatedly constructed from scratch, and therefore encourages experimentation. A number of transforms are provided for manipulating and analysing the graph, using various algorithms such as Louvain method, Betweenness centrality and k-NN.

Given Graphia's raison d'être of creating graphs from large and complex datasets, it follows that it is able to equivalently visualize very large graphs. This capability is obviously hardware dependent, but at the top end graphs consisting of millions of nodes and edges are successfully rendered. Furthermore, the visualization is (optionally) presented in 3D which can illuminate structure not otherwise apparent.

See Also

References

  1. ^ https://github.com/graphia-app/graphia/releases/tag/1.0 Graphia 1.0 release date
  2. ^ https://github.com/graphia-app/graphia/releases/tag/2.2 Graphia 2.2 release date
  3. ^ Freeman, Tom C.; Horsewell, Sebastian; Patir, Anirudh; Harling-Lee, Josh; Regan, Tim; Shih, Barbara B.; Prendergast, James; Hume, David A.; Angus, Tim (3 September 2020). "Graphia: A platform for the graph-based visualisation and analysis of complex data". bioRxiv 10.1101/2020.09.02.279349.
  4. ^ Thwaites, Ryan S.; Sanchez Sevilla Uruchurtu, Ashley; Siggins, Matthew K.; Liew, Felicity; Russell, Clark D.; Moore, Shona C.; Fairfield, Cameron; Carter, Edwin; Abrams, Simon; Short, Charlotte-Eve; Thaventhiran, Thilipan; Bergstrom, Emma; Gardener, Zoe; Ascough, Stephanie; Chiu, Christopher; Docherty, Annemarie B.; Hunt, David; Crow, Yanick J.; Solomon, Tom; Taylor, Graham P.; Turtle, Lance; Harrison, Ewen M.; Dunning, Jake; Semple, Malcolm G.; Baillie, J. Kenneth; Openshaw, Peter J. M. (10 March 2021). "Inflammatory profiles across the spectrum of disease reveal a distinct role for GM-CSF in severe COVID-19". Science Immunology. 6 (57). American Association for the Advancement of Science (AAAS): eabg9873. doi:10.1126/sciimmunol.abg9873. ISSN 2470-9468.
  5. ^ Dimonaco, Nicholas J.; Salavati, Mazdak; Shih, Barbara B. (30 December 2020). "Computational Analysis of SARS-CoV-2 and SARS-Like Coronavirus Diversity in Human, Bat and Pangolin Populations". Viruses. 13 (1). MDPI AG: 49. doi:10.3390/v13010049. ISSN 1999-4915.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  6. ^ Pridans, Clare; Irvine, Katharine M.; Davis, Gemma M.; Lefevre, Lucas; Bush, Stephen J.; Hume, David A. (1 February 2021). "Transcriptomic Analysis of Rat Macrophages". Frontiers in Immunology. 11. Frontiers Media SA. doi:10.3389/fimmu.2020.594594. ISSN 1664-3224.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  7. ^ Bartley, Kathryn; Chen, Wan; Lloyd Mills, Richard I.; Nunn, Francesca; Price, Daniel R. G.; Rombauts, Stephane; Van de Peer, Yves; Roy, Lise; Nisbet, Alasdair J.; Burgess, Stewart T. G. (7 April 2021). "Transcriptomic analysis of the poultry red mite, Dermanyssus gallinae, across all stages of the lifecycle". BMC Genomics. 22 (1). Springer Science and Business Media LLC. doi:10.1186/s12864-021-07547-9. ISSN 1471-2164.{{cite journal}}: CS1 maint: unflagged free DOI (link)
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