Royal College of Surgeons in Ireland
Browse
1/1
2 files

Violin SuperPlots: visualizing replicate heterogeneity in large data sets.

Version 3 2021-10-11, 14:53
Version 2 2021-07-29, 11:42
Version 1 2021-07-29, 11:17
journal contribution
posted on 2021-07-29, 11:17 authored by Martin Kenny, Ingmar SchoenIngmar Schoen
A recent article in MBoC (Goedhart, 2021) presented a web interface for the creation of ‘SuperPlots’. SuperPlots were introduced by Lord and colleagues last year (Lord et al., 2020) to visualise both cell-level variability within replicates as well as the experimental reproducibility between replicates in one single plot. Simple bar charts or boxplots of mean or median values from experimental replicates mask the contribution of underlying cell-to-cell variations in individual experiments, whereas pooling cell-level data across replicates overemphasises statistical differences. The SuperPlot put forward by Lord et al. uses a beeswarm plot to display the cell-level data color-coded according to the individual replicates, and overlays the mean (or median) and error bars (standard deviation or confidence intervals) of each replicate (Figure 1a). The new web interface (Goedhart, 2021) offers an online option for researchers to generate beeswarm SuperPlots, as well as RainCloud plots (Allen et al., 2021), using their own data. We welcome the transparency brought by SuperPlots and would like to introduce an augmentation, the Violin SuperPlot, to further simplify visual inspection of raw data containing large sample sizes.

Funding

RCSI

History

Comments

The original article is available at https://www.molbiolcell.org

Published Citation

Kenny M, Schoen I. Violin SuperPlots: visualizing replicate heterogeneity in large data sets. Mol Biol Cell. 2021;32(15):1333-1334.

Publication Date

15 Jul 2021

PubMed ID

34264756

Department/Unit

  • School of Pharmacy and Biomolecular Sciences

Research Area

  • Vascular Biology
  • Biomaterials and Regenerative Medicine

Publisher

American Society for Cell Biology (ASCB)

Version

  • Accepted Version (Postprint)