RT Journal Article SR Electronic T1 Kronos: a workflow assembler for genome analytics and informatics JF bioRxiv FD Cold Spring Harbor Laboratory SP 040352 DO 10.1101/040352 A1 M Jafar Taghiyar A1 Jamie Rosner A1 Diljot Grewal A1 Bruno Grande A1 Radhouane Aniba A1 Jasleen Grewal A1 Paul C Boutros A1 Ryan D Morin A1 Ali Bashashati A1 Sohrab Shah YR 2016 UL http://biorxiv.org/content/early/2016/02/19/040352.abstract AB Background The field of next generation sequencing informatics has matured to a point where algorithmic advances in sequence alignment and individual feature detection methods have stabilized. Practical and robust implementation of complex analytical workflows (where such tools are structured into ‘best practices’ for automated analysis of NGS datasets) still requires significant programming investment and expertise.Results We present Kronos, a software platform for automating the development and execution of reproducible, auditable and distributable bioinformatics workflows. Kronos obviates the need for explicit coding of workflows by compiling a text configuration file into executable Python applications. The framework of each workflow includes a run manager to execute the encoded workflows locally (or on a cluster or cloud), parallelize tasks, and log all runtime events. Resulting workflows are highly modular and configurable by construction, facilitating flexible and extensible meta-applications which can be modified easily through configuration file editing. The workflows are fully encoded for ease of distribution and can be instantiated on external systems, promoting and facilitating reproducible research and comparative analyses. We introduce a framework for building Kronos components which function as shareable, modular nodes in Kronos workflows.Conclusion The Kronos platform provides a standard framework for developers to implement custom tools, reuse existing tools, and contribute to the community at large. Kronos is shipped with both Docker and Amazon AWS machine images. It is free, open source and available through PyPI (Python Package Index) and https://github.com/jtaghiyar/kronos.