2018
DOI: 10.1080/10618600.2017.1366914
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SinaPlot: An Enhanced Chart for Simple and Truthful Representation of Single Observations Over Multiple Classes

Abstract: Recent developments in data driven science, in particular computational biology, have led scientists to integrate data from several sources, over diverse experimental procedures, or databases. This alone poses a major challenge in truthfully visualising data, especially when the amount of data points varies between classes. To aid the presentation of datasets with differing sample size we have developed a new type of plot overcoming limitations of current standard visualization charts. Plots like bar charts, v… Show more

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Cited by 42 publications
(30 citation statements)
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“…Models from all other collections are grouped in several fragmented but distinct clusters. b-d, SinaPlots29 of each collection overlaid with box and whisker plots to indicate 25%, 50% (median) and 75% quantiles. GEMs from collections built in a modern automated pipeline (aGOra, carveMe, KBase) are stoichiometrically consistent, whereas models from the older Path2Models collection are up to 50% stoichiometrically inconsistent (b).…”
mentioning
confidence: 99%
“…Models from all other collections are grouped in several fragmented but distinct clusters. b-d, SinaPlots29 of each collection overlaid with box and whisker plots to indicate 25%, 50% (median) and 75% quantiles. GEMs from collections built in a modern automated pipeline (aGOra, carveMe, KBase) are stoichiometrically consistent, whereas models from the older Path2Models collection are up to 50% stoichiometrically inconsistent (b).…”
mentioning
confidence: 99%
“…The distribution of minimum pairwise patristic distances between individuals by various demographic factors were visualized using SinaPlots. 13 …”
Section: Methodsmentioning
confidence: 99%
“…Our goal here is not to propose a totally novel invention, but rather to make a powerful visualization strategy freely, easily, and transparently available across commonly used platforms. To this end, similar but distinct plotting strategies include beanplots (Kampstra, 2008), estimation plots (Ho, Tumkaya, Aryal, Choi, & Claridge-Chang, 2018), pirateplots (Phillips, 2016), sinaplots (Sidiropoulos et al, 2018), stripcharts (Chambers, 2017), beeswarm plots (Eklund, 2016), and many others. Our hope here is to offer a cross-platform, open science tool which builds upon these approaches and makes robust and transparent data-plotting available to as wide an audience as possible.…”
Section: Introductionmentioning
confidence: 99%