Pregled bibliografske jedinice broj: 628070
BioBlend - Enabling Pipeline Dreams
BioBlend - Enabling Pipeline Dreams // Bioinformatics Open Source Conference (BOSC 2013)
Berlin, Njemačka, 2013. (predavanje, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 628070 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
BioBlend - Enabling Pipeline Dreams
Autori
Sloggett, Clare ; Goonasekera, Nuwan ; Afgan, Enis
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Skup
Bioinformatics Open Source Conference (BOSC 2013)
Mjesto i datum
Berlin, Njemačka, 19.07.2013. - 20.07.2013
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
API; automation; bioinformatics analysis; Galaxy; CloudMan
Sažetak
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.
Izvorni jezik
Engleski
Znanstvena područja
Biologija, Računarstvo