engleski

BioBlend - Enabling Pipeline Dreams

Since the advent of high-throughput sequencing technologies, genomics has become a large-data science with immense opportunity for biological insight. However, the analysis of such data is technically challenging, and collaboration between biologists and bioinformaticians is required to interpret the data. Galaxy is a popular and accessible platform for bioinformatics analysis, which provides many advantages such as visualisation, interactive analysis, reproducibility, and data and workflow sharing via a graphical interface. CloudMan is a cloud-based job runtime platform, which allows researchers to easily provision scalable 'virtual clusters' to run Galaxy and other applications in a cloud computing environment. We created the BioBlend library, a unified API in a high-level language (python) that wraps the functionality of both Galaxy and CloudMan APIs. BioBlend exposes the programmable functionality of the two applications in a format that is more suitable for programming and thus makes it easier for bioinformaticians to automate end-to-end large-data analysis, from scratch. Because the end result of a data analysis is still available in the Galaxy environment, the resulting pipeline is highly accessible to collaborators. In combination with CloudMan, it is possible to both provision the required infrastructure, and automate complex analyses over large data sets on an as needed basis. The library is easily installable via PyPi and comes with detailed documentation and example scripts in both the project website and the source code. This talk will provide an overview of the library, details of the available functionality, and highlight some of the available scripts.

API; automation; bioinformatics analysis; Galaxy; CloudMan

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