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PlotsOfDifferences – a web app for the quantitative comparison of unpaired data

View ORCID ProfileJoachim Goedhart
doi: https://doi.org/10.1101/578575
Joachim Goedhart
*Swammerdam Institute for Life Sciences, Section of Molecular Cytology, van Leeuwenhoek Centre for Advanced Microscopy, University of Amsterdam, P.O. Box 94215, NL-1090 GE Amsterdam, The Netherlands
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Abstract

The quantitative comparison of data acquired under different conditions is an important aspect of experimental science. The most widely used statistic for quantitative comparisons is the p-value. However, p-values suffer from several shortcomings. The most prominent shortcoming that is relevant for quantitative comparisons is that p-values fail to convey the magnitude of differences. The differences between conditions are best quantified by the determination of effect size. To democratize the calculation of effect size, we have developed a web-based tool. The tool uses bootstrapping to resample mean or median values for each of the conditions and these values are used to calculate the effect size and their compatibility interval. The web tool generates a graphical output, showing the bootstrap distribution of the difference next to the actual data for optimal interpretation. A tabular output with statistics and effect sizes is also generated and the table can be supplemented with p-values that are calculated with a randomization test. The app that we report here is dubbed PlotsOfDifferences and is available at: https://huygens.science.uva.nl/PlotsOfDifferences

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Footnotes

  • ↵‡ Email: j.goedhart{at}uva.nl Twitter: @joachimgoedhart

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted March 17, 2019.
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PlotsOfDifferences – a web app for the quantitative comparison of unpaired data
Joachim Goedhart
bioRxiv 578575; doi: https://doi.org/10.1101/578575
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PlotsOfDifferences – a web app for the quantitative comparison of unpaired data
Joachim Goedhart
bioRxiv 578575; doi: https://doi.org/10.1101/578575

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