About the resource

Type of resource: Analysis workflow environment
License/availability: Open source
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User documentation: Click here to view documentation
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Yabi is an online research environment that provides rare disease researchers with an intuitive, easy to use web-based environment for creating, running and managing bioinformatics analysis workflows. Yabi implements standardised workflows seamlessly across a diverse range of –omics data for rare disease research. Through Yabi, it is possible to share workflows to accurately analyse and annotate –omics data.

One of the main challenges is to enable users seamless and transparent access to heterogenous computing environments across geographical locations. Yabi provides an analysis workflow environment that can create and reuse bioinformatics workflows as well as manage large amounts of both raw and processed data in a secure and flexible way. Yabi can be used for genomics, transcriptomics, proteomics and metabolomics data analysis. Yabi can be used via a web-based environment to drag-and-drop tools to create sophisticated workflows. It can also be accessed through the Yabi command line, which is designed for users that are more comfortable with writing scripts or for enabling external workflow environments to leverage the features in Yabi.

Configuring tools can be a significant overhead in workflow environments. Yabi greatly simplifies this task by enabling system administrators to configure as well as manage running tools via a web-based environment and without the need to write or edit software programs or scripts.

Yabi will enable both researchers and clinicians to access and run multi -omics analysis through its seamless point and click interface without the need for any knowledge of command–line computing. The ability to link geographically distributed resources allowing real-time collaboration and data exchange between RD-Connect partners for the establishment of shared standardised -omics analysis pipelines starting at the laboratory and ending at submission of the final data analysis to a data repository and/or disease registry. All of this is achieved with only a standard web browser.

In Yabi, we have established a pipeline enabling the extraction of exome data of an individual from EBI’s EGA Archive, the detection and annotation of variants from that exome and subsequent submission of candidate mutations from that individual into a disease registry. Also demonstrated is the ability to save and re-use Yabi workflows.