A data-driven weighting scheme for multivariate phenotypic endpoints recapitulates zebrafish developmental cascades.

ABSTRACT: Zebrafish have become a key alternative model for studying health effects of environmental stressors, partly due to their genetic similarity to humans, fast generation time, and the efficiency of generating high-dimensional systematic data. Studies aiming to characterize adverse health effects in zebrafish typically include several phenotypic measurements (endpoints). While there is a solid biomedical basis for capturing a comprehensive set of endpoints, making summary judgments regarding health effects requires thoughtful integration across endpoints. Here, we introduce a Bayesian method to quantify the informativeness of 17 distinct zebrafish endpoints as a data-driven weighting scheme for a multi-endpoint summary measure, called weighted Aggregate Entropy (wAggE). We implement wAggE usi

SUBMITTER: Zhang G 

PROVIDER: S-EPMC5224523 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature