SciPipe - A workflow library for agile development of complex and dynamic bioinformatics pipelines

Abstract

Background: The complex nature of biological data has driven the development of specialized sof ware tools. Scienti c work ow management systems simplify the assembly of such tools into pipelines, assist with job automation and aid reproducibility of analyses. Many contemporary work ow tools are specialized and not designed for highly complex work ows, such as with nested loops, dynamic scheduling and parametrization, which is common in e.g. machine learning.Findings: SciPipe is a work ow programming library implemented in the programming language Go, for managing complex and dynamic pipelines in bioinformatics, cheminformatics and other elds. SciPipe helps in particular with work ow constructs common in machine learning, such as extensive branching, parameter sweeps and dynamic scheduling and parametrization of downstream tasks. SciPipe builds on Flow-based programming principles to support agile development of work ows based on a library of self-contained, re-usable components. It supports running subsets of work ows for improved iterative development, and provides a data-centric audit logging feature that saves a full audit trace for every output le of a work ow, which can be converted to other formats such as HTML, TeX and PDF on-demand. The utility of SciPipe is demonstrated with a machine learning pipeline, a genomics, and a transcriptomics pipeline.Conclusions: SciPipe provides a solution for agile development of complex and dynamic pipelines, especially in machine leaning, through a exible programming API suitable for scientists used to programming or scripting.

Predicting Off-Target Binding Profiles With Confidence Using Conformal Prediction

“…The observations added as “assumed non-actives” were not included in the calibration set to avoid biasing the evaluation. The computational workflows for orchestrating the extraction of data, model building, and the collection of results for summarizing and plotting were implemented in the Go programming language using the SciPipe workflow library that is available as open source software at scipipe.org (Lampa et al, 2018b ). The cost values for each target are stored in the workflow code, available on GitHub (PTP, 2018 ).…”

Approaches for Containerized Scientific Workflows in Cloud Environments with Applications in Life Science

“…SciPipe [36] (SciPipe, RRID:SCR 017086) is a workflow library based on Flow-based programming principles, which enables building workflows from component libraries of predefined workflow components. SciPipe is implemented as a programming library in Go, which enables using the full power of the Go programming language to define workflows, as well as to compile workflows to executable files, for maximum ease of deployment in cloud scenarios.…”

SciPipe—Turning Scientific Workflows into Computer Programs

“…SciPipe [7] is designed from the start as a programming library embedded in the implementation language (Google's Go, or "Golang"), rather than inventing new textual syntax or graphical tools. It thus leverages the full power and flexibility of the Go programming language for implementing workflow logic.…”