ZFIN ID: ZDB-PUB-160502-1
Aggregate Entropy Scoring for Quantifying Activity across Endpoints with Irregular Correlation Structure
Zhang, G., Marvel, S., Truong, L., Tanguay, R.L., Reif, D.M.
Date: 2016
Source: Reproductive toxicology (Elmsford, N.Y.) 62: 92-9 (Journal)
Registered Authors: Tanguay, Robert L.
Keywords: Chemical Biology, Developmental Neurotoxicology, High Throughput Screening, Morphology, Multiplexed Assays, ToxCast, Zebrafish
MeSH Terms:
  • Animals
  • Embryo, Nonmammalian
  • Entropy
  • Flame Retardants/toxicity
  • High-Throughput Screening Assays*
  • Models, Theoretical*
  • Phenotype
  • Teratogens/toxicity*
  • Zebrafish/embryology*
PubMed: 27132190 Full text @ Reprod. Toxicol.
Robust computational approaches are needed to characterize systems-level responses to chemical perturbations in environmental and clinical toxicology applications. Appropriate characterization of response presents a methodological challenge when dealing with diverse phenotypic endpoints measured using in vivo systems. In this article, we propose an information-theoretic method named Aggregate Entropy (AggE) and apply it to scoring multiplexed, phenotypic endpoints measured in developing zebrafish (Danio rerio) across a broad concentration-response profile for a diverse set of 1,060 chemicals. AggE accurately identified chemicals with significant morphological effects, including single-endpoint effects and multi-endpoint responses that would have been missed by univariate methods, while avoiding putative false-positives that confound traditional methods due to irregular correlation structure. By testing AggE in a variety of high-dimensional real and simulated datasets, we have characterized its performance and suggested implementation parameters that can guide its application across a wide range of experimental scenarios.