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Abstract
Zebrafish have become an important alternative model for characterizing chemical bioactivity, partly due to the efficiency at which systematic, high-dimensional data can be generated. However, these new data present analytical challenges associated with scale and diversity. We developed a novel, robust statistical approach to characterize chemical-elicited effects in behavioral data from high-throughput screening (HTS) of all 1,060 Toxicity Forecaster (ToxCast™) chemicals across 5 concentrations at 120 hours post-fertilization (hpf). Taking advantage of the immense scale of data for a global view, we show that this new approach reduces bias introduced by extreme values yet allows for diverse response patterns that confound the application of traditional statistics. We have also shown that, as a summary measure of response for local tests of chemical-associated behavioral effects, it achieves a significant reduction in coefficient of variation compared to many traditional statistical modeling methods. This effective increase in signal-to-noise ratio augments statistical power and is observed across experimental periods (light/dark conditions) that display varied distributional response patterns. Finally, we integrated results with data from concomitant developmental endpoint measurements to show that appropriate statistical handling of HTS behavioral data can add important biological context that informs mechanistic hypotheses.
Highlights
A major focus of toxicological research is to develop high-throughput screening (HTS) assays to keep pace with the ever-increasing number of chemicals in commerce while retaining toxicity information, reducing the cost, and the use of animals [1]
Our method provided a consistent evaluation over the controls and significantly reduced the coefficient of variation compared to various traditional modeling methods, including mean movement, simple logarithm transformed mean movement, the third quartile movement, median movement, and the square root of mean movement (Fig 4B and 4C)
193 chemicals were only found significant in the light interval, 83 chemicals were only significant in the dark interval, and 80 chemicals were significant in both intervals
Summary
A major focus of toxicological research is to develop high-throughput screening (HTS) assays to keep pace with the ever-increasing number of chemicals in commerce while retaining toxicity information, reducing the cost, and the use of animals [1]. HTS in vitro assays, such as Toxicity Forecaster (ToxCast) and Toxicology Testing in the 21st Century (Tox21), were implemented to speed up the pace of chemical testing [2,3]. These target-specific technologies do not assay the systems-level bioactivity of chemicals. New strategies are needed to characterize the hazardous profiles of chemicals and provide complementary, systematic data in order to build computational models to advance toxicological research.
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