Abstract
Making comparisons between genome-wide association studies is a crucial practice in genetics. Despite this, conventional visualizations used in these studies tend to suffer from readability issues. These issues include, for instance, overcrowded data points and difficulties in supporting comparisons between different distributions. One of the most commonly used visualizations for this purpose, the traditional Manhattan plot, is visually optimized for comparing peaks only within one distribution of data points. In genetics research, however, there is often a need to compare multiple distributions. In this paper, we present a novel interaction model that relies on the use of zoomable heatmaps. This interaction model aims to support users in preliminary and straightforward cross-distribution comparisons through semantic zooming, heatmaps, and the overview+detail approach. All these interaction methods have their origin in map-based user interfaces and visualizations.
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MMP is available at https://geneviz.aalto.fi/MMP/2023/.
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References
Zack, M., Landry, E. (eds.): Research in History and Philosophy of Mathematics. PCSHPMSCPM, Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46615-6
Bertin, J.: Semiology of Graphics. University of Wisconsin Press, Madison (1983)
Boughton, A.P.,et al.: Locuszoom.js: interactive and embeddable visualization of genetic association study results. Bioinformatics (Oxford, England) 37(18), 3017–3018 (2021). https://doi.org/10.1093/bioinformatics/btab186
Boulos, M.N.K.: The use of interactive graphical maps for browsing medical/health Internet information resources. Int. J. Health Geogr. 2(1), 1 (2003). https://doi.org/10.1186/1476-072x-2-1
Cantor, R.M., Lange, K., Sinsheimer, J.S.: Prioritizing GWAS results: a review of statistical methods and recommendations for their application. Am. J. Hum. Genet. 86(1), 6–22 (2010). https://doi.org/10.1016/j.ajhg.2009.11.017
Cerioli, N., Vyas, R., Reeve, M.P., Masoodian, M.: Mapping the colocalization network: a wayfinding approach to interacting with complex network diagrams. In: Proceedings of the 26th International Conference Information Visualisation, pp. 186–193. IV ’22, IEEE (2022).https://doi.org/10.1109/IV56949.2022.00038
Cockburn, A., Karlson, A., Bederson, B.B.: A review of overview+detail, zooming, and focus+context interfaces. ACM Comput. Surv. 41(1) (2009). https://doi.org/10.1145/1456650.1456652
von Engelhardt, Y.: The language of graphics. Ph.D. thesis, Institute for Logic, Language and Computation, University of Amsterdam, September 2022. www.hdl.handle.net/11245/1.208097
Garlandini, S., Fabrikant, S.I.: Evaluating the effectiveness and efficiency of visual variables for geographic information visualization. In: Hornsby, K.S., Claramunt, C., Denis, M., Ligozat, G. (eds.) COSIT 2009. LNCS, vol. 5756, pp. 195–211. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-03832-7_12
Gel, B., Serra, E.: KaryoploteR: an R/Bioconductor package to plot customizable genomes displaying arbitrary data. Bioinformatics 33(19), 3088–3090 (2017). https://doi.org/10.1093/bioinformatics/btx346
Goris, A., et al.: No evidence for shared genetic basis of common variants in multiple sclerosis and amyotrophic lateral sclerosis. Hum. Mol. Genet. 23(7), 1916–1922 (2014). https://doi.org/10.1093/hmg/ddt574
Grace, C., Farrall, M., Watkins, H., Goel, A.: Manhattan++: displaying genome-wide association summary statistics with multiple annotation layers. BMC Bioinform. 20(1), 610 (2019). https://doi.org/10.1186/s12859-019-3201-y
Huang, K., et al.: Transcriptome-wide transmission disequilibrium analysis identifies novel risk genes for autism spectrum disorder. PLoS Genet. 17(2), e1009309 (2021). https://doi.org/10.1371/journal.pgen.1009309, publisher: Public Library of Science
Kaler, A.: Genomic and Physiological Approaches to Improve Drought Tolerance in Soybean. Ph.D. thesis, Department of Crop, Soil & Environmental Sciences, University of Arkansas (2017). www.scholarworks.uark.edu/etd/2490
Lucas, A., Verma, A., Ritchie, M.D.: Hudson: A User-Friendly R Package to Extend Manhattan Plots, January 2022. https://doi.org/10.1101/2022.01.25.474274
Luz, S., Masoodian, M.: Visualisation of parallel data streams with temporal mosaics. In: Proceedings of the 11th International Conference Information Visualization, pp. 197–202. IV ’07, IEEE (2007). https://doi.org/10.1109/IV.2007.127
Luz, S., Masoodian, M.: Comparing static GANTT and mosaic charts for visualization of task schedules. In: Proceedings of the 15th International Conference on Information Visualisation, pp. 182–187. IV ’11, IEEE (2011). https://doi.org/10.1109/IV.2011.53
Luz, S., Masoodian, M.: A comparison of linear and mosaic diagrams for set visualization. Inf. Vis. 18(3), 297–310 (2019). https://doi.org/10.1177/1473871618754343
Masoodian, M., Luz, S.: Map-based interfaces and interactions. In: Proceedings of the International Conference on Advanced Visual Interfaces, pp. 88:1–88:4. AVI ’22, Association for Computing Machinery, New York, NY, USA (2022). https://doi.org/10.1145/3531073.3535258
Masoodian, M., Luz, S.: Designing for map-based interfaces and interactions. In: Abdelnour Nocera, J., Kristin Larusdottir, M., Petrie, H., Piccinno, A., Winckler, M. (eds.) Human-Computer Interaction – INTERACT 2023. INTERACT 2023. Lecture Notes in Computer Science, vol. 14145, pp. 616–620. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-42293-5_82
Mägi, R., Morris, A.P.: GWAMA: software for genome-wide association meta-analysis. BMC Bioinform. 11(1), 288 (2010). https://doi.org/10.1186/1471-2105-11-288
Nielsen, C.B., Cantor, M., Dubchak, I., Gordon, D., Wang, T.: Visualizing genomes: techniques and challenges. Nat. Methods 7(3), S5–S15 (2010). https://doi.org/10.1038/nmeth.1422
Nkambule, L.L.: GwaRs: an R shiny web application for visualizing genome-wide association studies data, April 2020. https://doi.org/10.1101/2020.04.17.044784
Perlin, K., Fox, D.: Pad: an alternative approach to the computer interface. In: Proceedings of the 20th Annual Conference on Computer Graphics and Interactive Techniques, pp. 57–64. SIGGRAPH ’93, Association for Computing Machinery, New York, NY, USA (1993). https://doi.org/10.1145/166117.166125
The 1000 Genomes Project consortium: a global reference for human genetic variation. Nature 526(7571), 68–74 (2015). https://doi.org/10.1038/nature15393
Turner, S.D.: Qqman: an R package for visualizing GWAS results using Q-Q and manhattan plots, May 2014. https://doi.org/10.1101/005165
White, J.: Miamiplot: an R package for creating GGplot2 based Miami plots, August 2023. www.github.com/juliedwhite/miamiplot
Wilkinson, L., Friendly, M.: The history of the cluster heat map. Am. Stat. 63, 179–184 (2009). https://doi.org/10.1198/tas.2009.0033
Yang, J., Ward, M.O., Rundensteiner, E.A.: Interactive hierarchical displays: a general framework for visualization and exploration of large multivariate data sets. Comput. Graph. 27(2), 265–283 (2003). https://doi.org/10.1016/S0097-8493(02)00283-2
Yin, L.: CMplot, August 2023. www.github.com/YinLiLin/CMplot, original-date: 2015-05-26T08:57:29Z
Zhang, Y.W., et al.: MrMLM v4.0.2: an R platform for multi-locus genome-wide association studies. Genomics Proteomics Bioinform. 18(4), 481–487 (2020). https://doi.org/10.1016/j.gpb.2020.06.006
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Simeoni, F., Cerioli, N., Daly, M., Reeve, M.P., Vyas, R., Masoodian, M. (2024). Zoomable Heatmaps: Improving Manhattan Plots to Compare Multiple Genome-Wide Studies. In: Bramwell-Dicks, A., Evans, A., Winckler, M., Petrie, H., Abdelnour-Nocera, J. (eds) Design for Equality and Justice. INTERACT 2023. Lecture Notes in Computer Science, vol 14536. Springer, Cham. https://doi.org/10.1007/978-3-031-61698-3_14
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