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http://dx.doi.org/10.9717/kmms.2022.25.2.363

Visualization for Integrated Analysis of Multi-Omics Data by Harmful Substances Exposed to Human  

Shin, Ga-Hee (Insilicogen Inc.)
Hong, Ji-Man (Insilicogen Inc.)
Park, Seo-Woo (Insilicogen Inc.)
Kang, Byeong-Chul (DiF Inc.)
Lee, Bong-Mun (CKU center for health policy research., Catholic Kwandong University)
Publication Information
Journal of Korea Multimedia Society / v.25, no.2, 2022 , pp. 363-373 More about this Journal
Abstract
Multi-omics data is difficult to interpret due to the heterogeneity of information by the volume of data, the complexity of characteristics of each data, and the diversity of omics platforms. There is not yet a system for interpreting to visualize research data on environmental diseases concerning environmental harmful substances. We provide MEE, a web-based visualization tool, to comprehensively explore the complexity of data due to the interconnected characteristics of high-dimensional data sets according to exposure to various environmental harmful substances. MEE visualizes omics data of correlation between omics data, subjects and samples by keyword searches of meta data, multi-omics data, and harmful substances. MEE has been demonstrated the versatility by two examples. We confirmed the correlation between smoking and asthma with RNA-seq and Methylation-Chip data, it was visualized that genes (P HACTR3, PXDN, QZMB, SOCS3 etc.) significantly related to autoimmune or inflammatory diseases. To visualize the correlation between atopic dermatitis and heavy metals, we selected 32 genes related immune response by integrated analysis of multi-omics data. However, it did not show a significant correlation between mercury in blood and atopic dermatitis. In the future, should continuously collect an appropriate level of multi-omics data in MEE system, will obtain data to analyze environmental substances and diseases.
Keywords
Multi-Omics; Exposure; Web-based Visualization; Environmental Harmful Substance; Integrated Analysis;
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