Beyond Global Correlations



Correlations are one of the most commonly used statistics that quantify the dependence between two variables. Although global correlations can be calculated across all the data points collected in a study, some distinct and important local and context-dependent patterns may be masked by global measures. In this presentation, we will discuss the need, benefit, and challenges in inferring local and context-dependent correlations in genetics and genomics studies. We will focus on examples on local genetic correlations to identify genomic regions with shared effects on different complex traits and cell-type-specific correlations to identify co-regulated genes in disease-relevant cell types.