Aggregate entropy scoring for quantifying activity across endpoints with irregular correlation structure.

TitleAggregate entropy scoring for quantifying activity across endpoints with irregular correlation structure.
Publication TypeJournal Article
Year of Publication2016
AuthorsZhang, G, Marvel, S, Truong, L, Tanguay, RL, Reif, DM
JournalReprod Toxicol
Volume62
Pagination92-9
Date Published2016 Jul
ISSN1873-1708
Abstract

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 1060 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.

DOI10.1016/j.reprotox.2016.04.012
Alternate JournalReprod. Toxicol.