Session 7: Phenotypes and Diseases ACM-BCB’18, August 29-September 1, 2018, Washington, DC, USA Detecting Divergent Subpopulations in Phenomics Data using Interesting Flares Methun Kamruzzaman Ananth Kalyanaraman Bala Krishnamoorthy Washington State University Washington State University Washington State University Pullman, Washington Pullman, Washington Vancouver, Washington
[email protected] [email protected] [email protected] ABSTRACT 1 INTRODUCTION One of the grand challenges of modern biology is to understand Advances in agricultural and biomedical sciences for the next decade how genotypes (G) and environments (E) interact to affect pheno- are poised to be driven by the increasing availability of data gen- types (P), i.e., G × E ! P. Phenomics is the emerging field that aims erated by high-throughput technologies. In precision agriculture, to study large and complex data sets encompassing combinations of in addition to genotypic data generated using DNA sequencing {genotypes, environments, phenotypes} readings. A phenomenon of technologies, massive volumes of data are also being gathered from crucial interest in this context is that of divergent subpopulations, i.e., various field sensing technologies that measure crop phenotypes how certain subgroups of the population show differential behavior (e.g., plant height, pollen shed) alongside environmental variables under different types of environmental conditions. We consider the (e.g., temperature, humidity, soil pH, etc.). In the field of medicine, fundamental task of identifying such “interesting” subpopulation- a diverse range of data is being collected on patient genotypes level behavior by analyzing high-dimensional phenomics data sets along with a multitude of disease- and treatment-related pheno- from a large and diverse population.