Automating data management and analyses in sequencing facilities using a Django-based LIMS

The increasing complexity and volume of data generated in sequencing facilities necessitate robust solutions for data management and analysis. We present an integrated approach to automating data processing, analysis, and management by combining a Django-based Laboratory Information Management System (LIMS) with a Nextflow pipeline. The LIMS facilitates efficient tracking and management of samples, projects, and instrument runs, while the Nextflow pipeline automates the execution of demultiplexing, quality control, and data transfer. By integrating these systems, we achieved seamless data flow, ensuring reproducibility and reducing manual errors. Furthermore, leveraging containerization and HPC computing with Nextflow enhances the scalability and portability of the procedures. This combined approach provides a comprehensive solution for sequencing facilities, streamlining both data management and computational processes, ultimately accelerating biomedical research and discoveries.