Abstract

The Sequence Read Archive (SRA), the world's largest database of sequences, hosts approximately 10 petabases (1016 bp) of sequence data and is growing at the alarming rate of 10 TB per day. Yet this rich trove of data is inaccessible to most researchers: searching through the SRA requires large storage and computing facilities that are beyond the capacity of most laboratories. Enabling scientists to analyze existing sequence data will provide insight into ecology, medicine, and industrial applications. In this project we specifically focus on metagenomic sequences (whole community data sets from different environments). We are developing a set of tools to enable biologists to mine the metagenomes in the SRA using the NSF-funded cloud computing resources, Jetstream and Wrangler. We have developed a proof-of-principle pipeline to demonstrate the feasibility of the approach. We are leveraging our existing …

Date

2018

Authors

Kyle Levi, Mats Rynge, Eroma Abeysinghe, Robert A Edwards

Book

Proceedings of the Practice and Experience on Advanced Research Computing: Seamless Creativity

Pages

1-7