PlotsOfData—A web app for visualizing data together with their summaries

Postma, Marten; Goedhart, Joachim

doi:10.1371/journal.pbio.3000202

Cited by 510 publications

(283 citation statements)

References 18 publications

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“…We recommend the use of PlotsOfData (Postma & Goedhart, ) to measure statistical parameters such as mean, standard deviation, median, and 95% confidence intervals. We found that for measuring the microtubule growth and shrinkage speeds, about 20 to 50 trajectories were enough to find an accurate value, i.e., the standard deviation of speeds could not be further minimized by adding more trajectories.…”

Section: Commentarymentioning

confidence: 99%

“…6. The data can now be analyzed using standard spreadsheet programs or online tools, such as PlotsOfData (Postma & Goedhart, 2019). Typical growth and shrink speeds in Arabidopsis hypocotyls lie in the range of several dozens of nanometers per second.…”

Section: Of 14mentioning

confidence: 99%

“…(D) The resultant data can be analyzed using standard statistical tools. Here, a violin plot indicating the median (horizontal line) and 95% confidence intervals of the median (vertical bar) of the growth and shrink speed is generated using PlotsOfData(Postma & Goedhart, 2019).…”

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confidence: 99%

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Quantification of Cytoskeletal Dynamics in Time‐Lapse Recordings

2019

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The cytoskeleton is key to many essential processes in a plant cell, e.g., growth, division, and defense. Contrary to what “skeleton” implies, the cytoskeleton is highly dynamic, and is able to re‐organize itself continuously. The advent of live‐cell microscopy and the development of genetically encoded fluorophores enabled detailed observation of the organization and dynamics of the cytoskeleton. Despite the biological importance of the cytoskeletal dynamics, quantitative analyses remain laborious endeavors that only a handful of research teams regularly conduct. With this protocol, we provide a standardized step‐by‐step guide to analyze the dynamics of microtubules. We provide example data and code for post‐processing in Fiji that enables researchers to modify and adapt the routine to their needs. More such tools are needed to quantitatively assess the cytoskeleton and thus to better understand cell biology. © 2019 by John Wiley & Sons, Inc.

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confidence: 99%

Section: Of 14mentioning

confidence: 99%

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Quantification of Cytoskeletal Dynamics in Time‐Lapse Recordings

2019

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“…For static conditions, dotplots are a good way to graphically depict the data. Several online data visualization tools have been reported that include the option to display the actual data (Weissgerber et al, 2017;Postma and Goedhart, 2019;Goedhart, 2019;Ho et al, 2019). However, similar online tools for the visualization of continuous data seem (to the best of our knowledge) to be lacking.…”

Section: Introductionmentioning

confidence: 99%

“…Ideally, a data visualization tool for time-series data would be freely available, open source and generate high quality graphs that are publication ready. Having previously reported such a webtool for static data (Postma and Goedhart, 2019) and given the enthusiastic response by the community, we were motivated to generate a webtool for time-series data. The new web-tool that we generated is dubbed PlotTwist, for plotting data from Time-lapse experiments With Indicators of conditions at Set Times.…”

Section: Introductionmentioning

confidence: 99%

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

Goedhart

2019

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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

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Hyperactive TORC1 sensitizes yeast cells to endoplasmic reticulum stress by compromising cell wall integrity

2019

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Edited by Michael IbbaAccumulation of misfolded proteins in the endoplasmic reticulum (ER) activates the unfolded protein response (UPR). Here, we investigated how the target of rapamycin complex 1 (TORC1) signaling cascade acts in parallel with the UPR to regulate ER stress sensitivity. Using Saccharomyces cerevisiae, we found that TORC1 signaling is attenuated during ER stress and constitutive activation of TORC1 increases sensitivity to ER stressors independently of the UPR. Transcriptome analysis revealed that TORC1 hyperactivation results in cell wall remodelling. Conversely, hyperactive TORC1 sensitizes cells to cell wall stressors, including the antifungal caspofungin. Elucidating the crosstalk between the UPR, cell wall integrity, and TORC1 signaling may uncover new paradigms through which the response to protein misfolding is regulated.

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PlotsOfData—A web app for visualizing data together with their summaries

Cited by 510 publications

References 18 publications

Quantification of Cytoskeletal Dynamics in Time‐Lapse Recordings

Quantification of Cytoskeletal Dynamics in Time‐Lapse Recordings

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

Hyperactive TORC1 sensitizes yeast cells to endoplasmic reticulum stress by compromising cell wall integrity

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