Multi-Omic Integrative Analysis

Multi-omics can better characterize a phenotype and the causes of a disease by identifying one or more genetic variants that affect causal gene expression levels. Several omic measurements may affect regulations of gene expressions, such as transcription factor binding sites, DNA methylation and even single nucleotide variants. Gathering and integrating these data may reveal novel findings among multiple samples (tissues, cells, or individuals in case–control studies) and provide deeper insights than single omic analyses.