PlotTwist - a web app for plotting and annotating time-series data

Abstract

The results from time-dependent experiments are often used to generate plots that visualize how the data evolves over time. To simplify state-of-the-art data visualization and annotation of data from such experiments, an open source tool was created with R/shiny that does not require coding skills to operate. The freely available web app accepts wide (spreadsheet) and tidy data and offers a range of options to normalize the data. The data from individual objects can be shown in three different ways: (i) lines with unique colors, (ii) small multiples and (iii) heatmap-style display. Next to this, the mean can be displayed with a 95% confidence interval for the visual comparison of different conditions. Several color blind friendly palettes are available to label the data and/or statistics. The plots can be annotated with graphical features and/or text to indicate any perturbations that were applied during the time-lapse experiments. All user-defined settings can be stored for reproducibility of the data visualization. The app is dubbed PlotTwist and is available online: https://huygens.science.uva.nl/PlotTwist

Identification and characterization of structural and regulatory cell-shape determinants inHaloferax volcanii

“…All graphs for data visualization, unless stated otherwise, were plotted using PlotTwist (80) and PlotsOfData (81).…”

Seeing β-arrestin in action: The role of β-arrestins in Histamine 1 Receptor signaling

“…Background subtractions, bleedthrough correction and calculation of the normalized ratio per time point per cell were done in Excel (Microsoft Office). All plots were prepared with the PlotTwist web app (Goedhart 2019). Plots show the average response as a thicker line and a ribbon for the 95% confidence interval around the mean.…”

Network Analysis Reveals the Molecular Bases of Statin Pleiotropy That Vary with Genetic Background

“…Three centrality measurements were calculated: (i) degree centrality, which computes the number of edges linked to each node so that a node with degree 5 has 5 edges associated, that is, it is linked to 5 other nodes ( 32 ); (ii) closeness centrality, which corresponds to the average shortest path length of one node to every other node computed by the Newman method ( 33 ), where 0 means an isolated node and 1 is the highest centrality and connectivity; and (iii) betweenness centrality, which is the probability of passing through a node when using the shortest path length between two nodes and is computed with the highly precise algorithm developed by Brandes ( 34 ) to distinguish nodes critical to maintain a network. The three measurements of centrality were visualized as three-dimensional (3D) plots using R ( 94 ).…”