P1003 Reference Genome Alignment and Downstream Analyses Using Cloud Computing

Yinbing Ge , The Samuel Roberts Noble Foundation, Inc., Ardmore, OK
Mingyi Wang , The Samuel Roberts Noble Foundation, Inc., Ardmore, OK
Ji He , The Samuel Roberts Noble Foundation, Inc., Ardmore, OK
Analyses of large-scale sequences from next-generation sequencing (NGS) platforms are typically computational and memory intensive, requiring costly computing infrastructure. By allowing a large population of users to share virtually unlimited computing capacity, cloud computing offers cost-effective high-performance computing services and hence has become increasingly applausive to small-to-medium-sized research groups and institutes. One of the current obstacles for the NGS community is that there is a lack of user-intuitive sequence analyses tools for the not-so-computer-savvy, general biologists to benefit from cloud computing with minimal training on the various IT implications related to cloud computing. To tackle this, we developed a Microsoft Windows-based software tool that integrates multiple analytical functions for reference genome alignment, single-nucleotide polymorphism (SNP) analysis, and gene expression analysis. The software takes use of the Microsoft Azure cloud computing platform to carry out high performance computation. It at the same time allows users to conduct small-scale analyses using their local computer power. Additionally, the software offers a user-friendly genome browser-style visualization interface for users to investigate and interpret the analytical results. The software tool is currently pending publication, after which, will be freely available to the public. During the interim, it is available upon request.