ABSTRACT
This chapter introduces some approaches to analyze studies with multiomic data. These are studies that, for instance, have collected genomic, transcriptomic and exposomic data, or other types of omic data, on the same individuals. Data integration, also known as integrative bioinformatics, integrated analysis, crossomics, multi-dataset analysis or data fusion, includes the computational combination of datasets or the joint analysis of different tables, from different measurement modalities. The chapter describes how to perform genomic variation, domain-knowledge and multivariate analyses of multiomic studies. The multi-stage approach is based on two different strategies: genomic variation and domain-knowledge analyses. A domain-knowledge analysis for genomic data is, for instance, the selection of candidate single nucleotide polymorphisms for a trait from multiple public databases, such as the Genome-wide association studie catalog. The chapter provides a formal test to verify whether any feature or genomic region overlaps with any region of interest or feature.
