PhenoCurve: capturing dynamic phenotype-environment relationships using phenomics data

• DOI: 10.1093/bioinformatics/btw673
• Publication Date: 2016-10-21T19:05:23Z
• Authors: Yifan Yang; Lei Xu; Zheyun Feng; Jeffrey A Cruz; Linda J Savage; David M Kramer; Jin Chen
• Keywords: Phenomics; Phenotypic trait

Abstract Motivation Phenomics is essential for understanding the mechanisms that regulate or influence growth, fitness, and development. Techniques have been developed to conduct high-throughput large-scale phenotyping on animals, plants humans, aiming bridge gap between genomics, gene functions traits. Although new developments in techniques are exciting, we limited by tools analyze fully massive phenotype data, especially dynamic relationships phenotypes environments. Results We present a algorithm called PhenoCurve, knowledge-based curve fitting algorithm, identify complex environments, thus studying both values trends of phenomics data. The results real simulated data showed PhenoCurve has best performance among all six tested methods. Its application photosynthesis hysteresis pattern identification reveals core genes control photosynthetic efficiency response varying environmental conditions, which critical plant energy storage improving crop productivity. Availability Implementation Software available at phenomics.uky.edu/PhenoCurve Supplementary information Bioinformatics online.