GENESIS—Cloud-Based System for Next Generation Sequencing Analysis: A Proof of Concept

Authors: Maider Alberich Inchausti Arkaitz Artetxe Vallejo Eduardo Santamaria-Navarro Alfons Nonell-Canals Grégory Maclair

Date: 04.06.2016


Abstract

With the advent of the technology, the DNA sequencing has become cheaper and faster. Next-Generation Sequencing platforms are providing new opportunities to address biological and medical issues. However, they present new challenges of storing, handling and processing, as they produce massive amounts of data. Powerful computational infrastructure, new bioinformatics softwares and skilled people in programming are required to work with the analysis tools. This project aims to design and develop an intelligent system that analyses high-throughput datasets, with the purpose of improving the effectiveness in the biological and medical research fields. The target is to make a user-friendly tool that allows the user to automatically or manually design the desired analysis workflow. Therefore, the technological challenges consist in: (i) an interface between clinician and bioinformatics language, (ii) an intelligent tool that selects the appropriate analysis workflow and (iii) a solution that can handle, store and manage big datasets at a reasonable-price. In order to tackle these bottlenecks, a cloud-based prototype enhanced by a graphical user-friendly interface and implemented using Amazon Web Service.

BIB_text

@Article {
title = {GENESIS—Cloud-Based System for Next Generation Sequencing Analysis: A Proof of Concept},
pages = {291-300},
volume = {60},
keywds = {

Next generation sequencing (NGS) High-throughput sequencing Automatized workflow Cloud-computing Amazon web services (AWS)


}
abstract = {

With the advent of the technology, the DNA sequencing has become cheaper and faster. Next-Generation Sequencing platforms are providing new opportunities to address biological and medical issues. However, they present new challenges of storing, handling and processing, as they produce massive amounts of data. Powerful computational infrastructure, new bioinformatics softwares and skilled people in programming are required to work with the analysis tools. This project aims to design and develop an intelligent system that analyses high-throughput datasets, with the purpose of improving the effectiveness in the biological and medical research fields. The target is to make a user-friendly tool that allows the user to automatically or manually design the desired analysis workflow. Therefore, the technological challenges consist in: (i) an interface between clinician and bioinformatics language, (ii) an intelligent tool that selects the appropriate analysis workflow and (iii) a solution that can handle, store and manage big datasets at a reasonable-price. In order to tackle these bottlenecks, a cloud-based prototype enhanced by a graphical user-friendly interface and implemented using Amazon Web Service.


}
isbn = {978-3-319-39687-3},
doi = {10.1007/978-3-319-39687-3_28},
date = {2016-06-04},
year = {2016},
}
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