Searching the sequence read archive using Jetstream and Wrangler

Searching the sequence read archive using Jetstream and Wrangler. Levi, K., Abeysinghe, E., Rynge, M., & Edwards, R., A. In Proceedings of the Practice and Experience on Advanced Research Computing (PEARC '18), 7, 2018. Association for Computing Machinery.

Paper doi abstract bibtex

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 specifi- cally 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 in- frastructure to enable all scientists to access the SRA metagenomes regardless of their computational ability and are working to create a stable pipeline with a science gateway portal that is accessible to all researchers.تنيىسبت

@inproceedings{
 title = {Searching the sequence read archive using Jetstream and Wrangler},
 type = {inproceedings},
 year = {2018},
 keywords = {Apache Airavata,Bacteriophage,Credential Store,Jetstream,Metagenomics,Metagenomics Discovery Challenge,SRA,SRA Gateway,SciGaP,Search SRA,Sequence Read Archive,Wrangler},
 month = {7},
 publisher = {Association for Computing Machinery},
 day = {22},
 id = {13584977-03fc-35c2-b6e2-051a28161e0f},
 created = {2019-09-12T15:10:29.176Z},
 accessed = {2019-09-12},
 file_attached = {true},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {0e433c5b-85c4-32aa-851c-c145aac9f80f},
 last_modified = {2019-09-12T15:10:29.391Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 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 specifi- cally 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 in- frastructure to enable all scientists to access the SRA metagenomes regardless of their computational ability and are working to create a stable pipeline with a science gateway portal that is accessible to all researchers.تنيىسبت},
 bibtype = {inproceedings},
 author = {Levi, Kyle and Abeysinghe, Eroma and Rynge, Mats and Edwards, Robert A.},
 doi = {10.1145/3219104.3229278},
 booktitle = {Proceedings of the Practice and Experience on Advanced Research Computing (PEARC '18)}
}

Downloads: 0