Data

GapFinder Rocks

Commonwealth Scientific and Industrial Research Organisation
Ord, Louise ; Chua, Xin-Yi ; Bent, Stephen ; McGrath, Annette ; Lovell, David
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=http://hdl.handle.net/102.100.100/485406?index=1&rft.title=GapFinder Rocks&rft.identifier=http://hdl.handle.net/102.100.100/485406?index=1&rft.publisher=Commonwealth Scientific and Industrial Research Organisation&rft.description=This is an interactive example of the GapFinder approach to exploring large distance matrices that have a hierarchical structure to their observations. Applied to a small data sample representing forty geological observations, scalable strategies are presented that accurately visualise pairwise dissimilarities (or distances) between observations from a hierarchical taxonomy, in ways that use the most effective visual channel of the human visual system. \nLineage: This work was motivated by a need to explore distances between DNA sequences in relation to the Linnean taxonomy of biological classification and builds on the GapFinder work of Xin-Yi Chua et al. (2022). The interface implements the following R packages and their dependencies: rmarkdown, shiny, plotly, ggplot2, data.table, ggbeeswarm, ggdendro, scico, philentropy.&rft.creator=Ord, Louise &rft.creator=Chua, Xin-Yi &rft.creator=Bent, Stephen &rft.creator=McGrath, Annette &rft.creator=Lovell, David &rft.date=2023&rft.edition=v4&rft_rights=Creative Commons Attribution 4.0 International Licence https://creativecommons.org/licenses/by/4.0/&rft_rights=Data is accessible online and may be reused in accordance with licence conditions&rft_rights=All Rights (including copyright) CSIRO 2023.&rft_subject=data&rft_subject=visualisation&rft_subject=data visualisation&rft_subject=data analysis&rft_subject=data exploration&rft_subject=interactive&rft_subject=gapfinder&rft_subject=heatmap&rft_subject=dendrogram&rft_subject=beeswarm&rft_subject=dot plot&rft_subject=distributions&rft_subject=histogram&rft_subject=distance&rft_subject=matrices&rft_subject=taxonomy&rft_subject=clustering&rft_subject=dissimilarity&rft_subject=hierarchy&rft_subject=structure&rft_subject=shiny&rft_subject=plotly&rft_subject=Bioinformatics and computational biology not elsewhere classified&rft_subject=Bioinformatics and computational biology&rft_subject=BIOLOGICAL SCIENCES&rft_subject=Phylogeny and comparative analysis&rft_subject=Evolutionary biology&rft_subject=Data visualisation and computational (incl. parametric and generative) design&rft_subject=Design&rft_subject=BUILT ENVIRONMENT AND DESIGN&rft_subject=Applications in life sciences&rft_subject=Applied computing&rft_subject=INFORMATION AND COMPUTING SCIENCES&rft_subject=Applications in physical sciences&rft_subject=Data engineering and data science&rft_subject=Data management and data science&rft.type=dataset&rft.language=English Access the data
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Brief description

This is an interactive example of the GapFinder approach to exploring large distance matrices that have a hierarchical structure to their observations. Applied to a small data sample representing forty geological observations, scalable strategies are presented that accurately visualise pairwise dissimilarities (or distances) between observations from a hierarchical taxonomy, in ways that use the most effective visual channel of the human visual system.
Lineage: This work was motivated by a need to explore distances between DNA sequences in relation to the Linnean taxonomy of biological classification and builds on the GapFinder work of Xin-Yi Chua et al. (2022). The interface implements the following R packages and their dependencies: rmarkdown, shiny, plotly, ggplot2, data.table, ggbeeswarm, ggdendro, scico, philentropy.

Available: 2023-05-13

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Applications in Life Sciences | Applications in Physical Sciences | Applied Computing | Biological Sciences | Built Environment and Design | Bioinformatics and Computational Biology | Bioinformatics and Computational Biology Not Elsewhere Classified | Data Engineering and Data Science | Data Management and Data Science | Data Visualisation and Computational (Incl. Parametric and Generative) Design | Design | Evolutionary Biology | Information and Computing Sciences | Phylogeny and Comparative Analysis | beeswarm | clustering | data | data analysis | data exploration | data visualisation | dendrogram | dissimilarity | distance | distributions | dot plot | gapfinder | heatmap | hierarchy | histogram | interactive | matrices | plotly | shiny | structure | taxonomy | visualisation |

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