MULTIDIMENSIONAL VISUALIZATION FOR MULTI-OMICS DATA ANALYSIS

Abstract

High-throughput studies of biological systems are rapidly accumulating a large body of omic-scale data. The analysis of data that constitute various types of omics (Genomics, Metagenomics, Transcriptomics and Proteomics) from different experiments, play a role in the process of asking new questions that correlate between different combinations of these types of data. Thus, a systemic view is needed that addresses the use of the integration of these omics. The visualization of information or the use of a multidimensional view is increasingly relevant in the multi-omics theme. This article seeks to demonstrate the analysis of the four most cited tools for the integration of large volumes of multi-omic data, with regard to multidimensional visualization, suggesting evaluation criteria for the development or even improvement of new tools.