TitleA New Statistical Approach to Characterize Chemical-Elicited Behavioral Effects in High-Throughput Studies Using Zebrafish.
Publication TypeJournal Article
Year of Publication2017
AuthorsZhang, G, Truong, L, Tanguay, RL, Reif, DM
JournalPLoS One
Date Published2017

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 (ToxCastâ„¢) 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.

Alternate JournalPLoS ONE
PubMed ID28099482
PubMed Central IDPMC5242475
Grant ListP30 ES025128 / ES / NIEHS NIH HHS / United States
U01 ES027294 / ES / NIEHS NIH HHS / United States
T32 ES007329 / ES / NIEHS NIH HHS / United States
RC4 ES019764 / ES / NIEHS NIH HHS / United States
P42 ES016465 / ES / NIEHS NIH HHS / United States
P30 ES000210 / ES / NIEHS NIH HHS / United States
P42 ES005948 / ES / NIEHS NIH HHS / United States