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. 2020 Jun 1;36(11):3602-3604.
doi: 10.1093/bioinformatics/btaa138.

Breeze: an integrated quality control and data analysis application for high-throughput drug screening

Swapnil Potdar  1 , Aleksandr Ianevski  1   2 , John-Patrick Mpindi  1 , Dmitrii Bychkov  1 , Clément Fiere  1 , Philipp Ianevski  1 , Bhagwan Yadav  1 , Krister Wennerberg  1   3 , Tero Aittokallio  1   2   4 , Olli Kallioniemi  1   5 , Jani Saarela  1 , Päivi Östling  1   5
Affiliations

Breeze: an integrated quality control and data analysis application for high-throughput drug screening

Swapnil Potdar et al. Bioinformatics. .

Abstract

Summary: High-throughput screening (HTS) enables systematic testing of thousands of chemical compounds for potential use as investigational and therapeutic agents. HTS experiments are often conducted in multi-well plates that inherently bear technical and experimental sources of error. Thus, HTS data processing requires the use of robust quality control procedures before analysis and interpretation. Here, we have implemented an open-source analysis application, Breeze, an integrated quality control and data analysis application for HTS data. Furthermore, Breeze enables a reliable way to identify individual drug sensitivity and resistance patterns in cell lines or patient-derived samples for functional precision medicine applications. The Breeze application provides a complete solution for data quality assessment, dose-response curve fitting and quantification of the drug responses along with interactive visualization of the results.

Availability and implementation: The Breeze application with video tutorial and technical documentation is accessible at https://breeze.fimm.fi; the R source code is publicly available at https://github.com/potdarswapnil/Breeze under GNU General Public License v3.0.

Contact: swapnil.potdar@helsinki.fi.

Supplementary information: Supplementary data are available at Bioinformatics online.

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Figures

Fig. 1.
Fig. 1.
Example outcome plots of Breeze application. (A) The technical quality is visualized by listing QC metrics such as Z’ and SSMD, along with bar plots, plate heat maps and scatterplot of signal intensities of plate wells help in identifying distribution of controls and pinpoint outliers. (B) Drug quantification visualization in form of interactive heatmap and circular plots. The heatmap shows efficacies of the drugs (higher in red and lower in white) across different samples along with drug names and potential drug targets. Hovering over the heatmap shows individual dose–response curves of specific drugs
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