Journal of Cheminformatics (Mar 2023)

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/10.1186/s13321-023-00717-9
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 7

Abstract

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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. Graphical Abstract

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