Report generation was implemented within the existing Ruby on Rails (RoR) application by integrating an R engine. This integration allowed for the dynamic triggering of the R engine with customizable parameters. The Reports themselves were generated as HTML in R and seamlessly rendered within the RoR application. To enhance the overall application architecture and streamline file processing, improvements were made to reduce complexity. These enhancements resulted in improved efficiency and reduced the time required to generate and load the Reports. Additionally, the deployment of the application using Docker containers in the cloud significantly improved maintainability and availability.

The client is a growing genetic engineering firm that is a leader in RNA splicing error research and development. The client wanted to create a remedy for RNA splicing faults using analytics predictions in order to boost their developments in RNA research and therapies.

The client had a pre-existing application to assist in the identification, cataloguing, and interpretation of RNA patterns. However, they ran into performance problems when generating reports for experiment findings, which wasted a lot of time. They were motivated to deal with these difficulties and boost the effectiveness of their procedures.