Multi-omics Data Integration, Interpretation, and Its Application

作者：Indhupriya Subramanian, Srikant Prasad Verma, Shiva Kumar, Abhay Jere, Krishanpal Anamika · 发表于：Bioinformatics and Biology Insights · 年份：2020 · DOI：10.1177/1177932219899051 · 被引用次数：1678 · 研究领域：Bioinformatics and Genomic Networks、Gene expression and cancer classification、Microbial Metabolic Engineering and Bioproduction

To study complex biological processes holistically, it is imperative to take an integrative approach that combines multi-omics data to highlight the interrelationships of the involved biomolecules and their functions. With the advent of high-throughput techniques and availability of multi-omics data generated from a large set of samples, several promising tools and methods have been developed for data integration and interpretation. In this review, we collected the tools and methods that adopt integrative approach to analyze multiple omics data and summarized their ability to address applications such as disease subtyping, biomarker prediction, and deriving insights into the data. We provide the methodology, use-cases, and limitations of these tools; brief account of multi-omics data repositories and visualization portals; and challenges associated with multi-omics data integration.