Breeze 2.0: an interactive web-tool for visual analysis and comparison of drug response data

Abstract

Functional precision medicine (fPM) offers an exciting, simplified approach to finding the right applications for existing molecules and enhancing therapeutic potential. Integrative and robust tools ensuring high accuracy and reliability of the results are critical. In response to this need, we previously developed Breeze, a drug screening data analysis pipeline, designed to facilitate quality control, dose-response curve fitting, and data visualization in a user-friendly manner. Here, we describe the latest version of Breeze (release 2.0), which implements an array of advanced data exploration capabilities, providing users with comprehensive post-analysis and interactive visualization options that are essential for minimizing false positive/negative outcomes and ensuring accurate interpretation of drug sensitivity and resistance data. The Breeze 2.0 web-tool also enables integrative analysis and cross-comparison of user-uploaded data with publicly available drug response datasets. The updated version incorporates new drug quantification metrics, supports analysis of both multi-dose and single-dose drug screening data and introduces a redesigned, intuitive user interface. With these enhancements, Breeze 2.0 is anticipated to substantially broaden its potential applications in diverse domains of fPM.

Graphical Abstract

Figure 1.

General workflow of Breeze 2.0 web-application. (A) Breeze data analysis starts with a quality control (QC) procedure that includes multiple plate control-based QC metrics, such as Z-prime and SSMD (middle panel). Additionally, Breeze features a range of plate-specific visualizations, e.g. scatterplots (right panel), facilitating the detection of anomalies and experimental errors not identified through numerical analysis alone. In this example, Plate #2 demonstrates a poor quality, as evidenced by its low Z-prime score and high standard deviations of positive controls (red highlights in the middle panel). (B) Drug dose-response curve fitting is the first step in quantifying drug responses into single metrics (left panel). Subsequently, Breeze 2.0 supports the calculation of various drug performance metrics, including IC50, EC50, AUC and DSS, allowing for direct comparisons between compounds and relative metrics, such as sDSS and SI index that allow for comparison between samples and controls. The barplot illustrates an example where the DSS score was used as the quantification metric (12). Additionally, Breeze offers the possibility to cross-compare user-provided data with previously reported drug responses incorporated into the Breeze database, serving as reference controls for comparison (right panel). (C) Next, an interactive heatmap is generated to compare drug responses across different samples (e.g. cell lines or experimental conditions), with sDSS scores shown as an example to highlight the selective efficacy of the drugs, while other metrics can also be used in the heatmap. (D) As an alternative to heatmap, statistically significant differences in drug responses between two groups of samples can be identified using a volcano plot.