Motivation
There is a growing appreciation for the importance and role of pleiotropy in genetic architecture, with new approaches for investigating pleiotropy across the genome in different but complementary ways. These studies have ranged in the organisms of study, from model organisms to humans, as well as a wide range of genetic variation (such as gene knockouts, SNPs, and CNVs) and phenotypes (such as quantitative, dichotomous, and intermediate phenotypes).
These studies are shifting the focus from the single-gene, single-phenotype paradigm to exposing the dynamic network that links gene products and metabolites to the complex landscape of interrelated phenotypes. To sharpen our understanding of this network and its role health and disease, we need new statistical, experimental, and visualization techniques.
This session will focus broadly on pleiotropy and computational methods for measuring and analyzing pleiotropy. It will bring together scientists with backgrounds investigating pleiotropy from different angles to discuss the current state and future of pleiotropy research.