● Determine the relative variability of molecular phenotypes.  ● Compare covariation networks across molecular phenotypes.  ● Determine if genes/proteins with loss of function mutations are expressed. E.g. examine regulatory features, mRNA levels, proteins levels.  ● Map QTLs for each molecular phenotype to determine where most functional genetic variation resides.  ● Construct integrative regulatory networks using ‘systems genomics’ approaches.  ● Connect regions of allele-specific chromatin accessibility, allele-specific methylation and allele-specific gene expression.  ● Integrated analysis of patterns of X-inactivation.  ● Quantify tissue-specific levels of somatic mutations and their relationship to heterogeneity in gene expression levels  ● Associate levels of methylation and expression at telomere maintenance genes (e.g., TERC, TERT, DKC1) with telomere length measurements.  ● Multi-omics enrichments of trait-associated variation.  ● Support holistic predictive modeling across molecular phenotypes.