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AbstractIn recent years, high throughput next generation omics data have been broadly used in many research fields. However, analyzing omics data is still very challenging, especially for researchers with less experience in bioinformatics, software, and programming. Omics data analysis workflows usually are composed of many processes involving different software tools that demand different compute resources. So, it is often difficult to perform a full workflow in an automated way, despite thatdoi:10.1101/475699 fatcat:lh2kmzhlrzgy7amyddni3zboym