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qHTSWaterfall: 3-dimensional visualization software for quantitative high-throughput screening (qHTS) data

Bryan Queme, John C. Braisted, Patricia Dranchak, James Inglese
doi: https://doi.org/10.1101/2022.06.15.496346
Bryan Queme
aNational Center for Advancing Translation Sciences, National Institutes of Health, Rockville, MD 20850
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John C. Braisted
aNational Center for Advancing Translation Sciences, National Institutes of Health, Rockville, MD 20850
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  • For correspondence: john.braisted@nih.gov
Patricia Dranchak
aNational Center for Advancing Translation Sciences, National Institutes of Health, Rockville, MD 20850
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James Inglese
aNational Center for Advancing Translation Sciences, National Institutes of Health, Rockville, MD 20850
bNational Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892
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Abstract

High throughput screening (HTS) is widely used in drug discovery and chemical biology to identify and characterize agents having pharmacologic properties often by evaluation of large chemical libraries. Standard HTS data can be simply plotted as an x-y graph usually represented as % activity of a compound tested at a single concentration vs compound ID, whereas quantitative HTS (qHTS) data incorporates a third axis represented by concentration. By virtue of the additional data points arising from the compound titration and the incorporation of logistic fit parameters that define the concentration-response curve, such as EC50 and Hill slope, qHTS data has been challenging to display on a single graph. Here we provide a flexible solution to the rapid plotting of complete qHTS data sets to produce a 3-axis plot we call qHTS Waterfall Plots. The software described here can be generally applied to any 3-axis dataset and is available as both an R package and an R shiny application.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/ncats/qHTSWaterfall

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-NC-ND 4.0 International license.
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Posted June 17, 2022.
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qHTSWaterfall: 3-dimensional visualization software for quantitative high-throughput screening (qHTS) data
Bryan Queme, John C. Braisted, Patricia Dranchak, James Inglese
bioRxiv 2022.06.15.496346; doi: https://doi.org/10.1101/2022.06.15.496346
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qHTSWaterfall: 3-dimensional visualization software for quantitative high-throughput screening (qHTS) data
Bryan Queme, John C. Braisted, Patricia Dranchak, James Inglese
bioRxiv 2022.06.15.496346; doi: https://doi.org/10.1101/2022.06.15.496346

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