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Iris-Eda: An Integrated Rna-Seq Interpretation System For Gene Expression Data Analysis, Brandon Monier, Adam Mcdermaid, Cankun Wang, Jing Zhao, Allison Miller, Anne Fennell, Qin Ma

Agronomy, Horticulture and Plant Science Faculty Publications

Next-Generation Sequencing has made available substantial amounts of large-scale Omics data, providing unprecedented opportunities to understand complex biological systems. Specifically, the value of RNA-Sequencing (RNA-Seq) data has been confirmed in inferring how gene regulatory systems will respond under various conditions (bulk data) or cell types (single-cell data). RNA-Seq can generate genome-scale gene expression profiles that can be further analyzed using correlation analysis, co-expression analysis, clustering, differential gene expression (DGE), among many other studies. While these analyses can provide invaluable information related to gene expression, integration and interpretation of the results can prove challenging. Here we present a tool called IRIS-EDA, …