To robustly facilitate the large-scale nature of the RNA-seq data processing described above for ~600 samples, we utilized RAPiD, an efficient and dependable RNA-seq pipeline manager that automates read alignment, quality control, and quantitative analyses of next-generation sequencing gene expression experiments. By closely integrating with the Apollo framework, RAPiD utilizes high-performance computing clusters and provides pipeline monitoring so that RAPiD runs are automatically tracked, QCd, and visualized on the Apollo Run Console web interface. Of note, RAPiD is designed to be an agile framework that is user-configurable via JSON-formatted “recipes” that define the set of tools and algorithms, and corresponding parameters, for running various pipelines. Thus, in this work, RAPiD easily permitted the addition of alternative splicing analyses by running MISO and custom post-processing of MISO results
