DolphinNext: A graphical user interface for creating, deploying and executing Nextflow pipelines

Abstract

The emergence of high throughput technologies that produce vast amounts of genomic data, such as next-generation sequencing (NGS) are transforming biological research. The dramatic increase in the volume of data makes analysis the main bottleneck for scientific discovery. The processing of high throughput datasets typically involves many different computational programs, each of which performs a specific step in a pipeline. Given the wide range of applications and organizational infrastructures, there is a great need for a highly-parallel, flexible, portable, and reproducible data processing frameworks. Flexibility ensures that pipelines can support a variety of applications without requiring one-off modifications. Portability ensures that users can leverage computationally available resources and work within economic constraints. Reproducibility warrants credibility to the results and is particularly challenging in the face of the sheer volume of data and the complexity of processing pipelines that vary widely between users.\n\nSeveral platforms currently exist for the design and execution of complex pipelines (e.g. Galaxy, GenePattern, GeneProf). Unfortunately, these platforms lack the necessary combination of parallelism, portability, flexibility and/or reproducibility that are required by the current research environment. To address these shortcomings, Nextflow was implemented to simplify portable, scalable, and reproducible scientific pipelines using containers. We have used Nextflow capabilities as leverage and developed a user interface, DolphinNext, for creating, deploying, and executing complex Nextflow pipelines for high throughput data processing. The guiding principle of DolphinNext is to facilitate the building and deployment of complex pipelines using a modular approach implemented in a graphical interface. DolphinNext provides: 1. A drag and drop user interface that abstracts pipelines and allows users to create pipelines without familiarity in underlying programming languages. 2. A user interface to monitor pipeline execution that allows the re-initiation of pipelines at intermediate steps 3. Reproducible pipelines with version tracking and stand-alone versions that can be run independently. 4. Seamless portability to distributed computational environments such as high-performance clusters or cloud computing environments.