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Our client found difficulties in visualizing, understanding, and annotating custom defined RNA splicing events through the open-source Integrative Genomics Viewer (IGV), along with other gene related information like splicing mutations, significant exons, stop codons, and more.
Arrayo implemented an automated data ingestion system based on Amazon Web Services (AWS) along with an end-to-end splicing events browser and visualization web application. Together with the client, we reviewed the pros and limitations of IGV to understand how to implement it better and designed an efficient data model to query millions of genetic data points. After evaluating different visualization libraries we picked Apache ECharts for its ease of use and performance. After this collaboration effort, Arrayo’s team designed and implemented a data model (1) flexible enough to accept new annotations (metadata) on-demand, given that those are custom-defined and highly subject to on-going enrichment, and (2) performant enough to present millions of data points to the user in a matter of seconds. We then transitioned to building a proof of concept, tuned it with the client, validated the final conceptual solution, implemented the proper infrastructure to support it, and deployed the fully containerized solution on a container management system.
The result was a highly scalable web application that allowed for smooth navigation through a huge amount of data points and displayed stacked annotations for a clean, complete, and contextualized understanding of the genetic regions users were looking at.