{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:42Z","timestamp":1772138082258,"version":"3.50.1"},"reference-count":3,"publisher":"Oxford University Press (OUP)","issue":"16","license":[{"start":{"date-parts":[[2016,10,28]],"date-time":"2016-10-28T00:00:00Z","timestamp":1477612800000},"content-version":"vor","delay-in-days":190,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,8,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Motivation: Public archives contain thousands of trillions of bases of valuable sequencing data. More than 40% of the Sequence Read Archive is human data protected by provisions such as dbGaP. To analyse dbGaP-protected data, researchers must typically work with IT administrators and signing officials to ensure all levels of security are implemented at their institution. This is a major obstacle, impeding reproducibility and reducing the utility of archived data.<\/jats:p>\n                  <jats:p>Results: We present a protocol and software tool for analyzing protected data in a commercial cloud. The protocol, Rail-dbGaP, is applicable to any tool running on Amazon Web Services Elastic MapReduce. The tool, Rail-RNA v0.2, is a spliced aligner for RNA-seq data, which we demonstrate by running on 9662 samples from the dbGaP-protected GTEx consortium dataset. The Rail-dbGaP protocol makes explicit for the first time the steps an investigator must take to develop Elastic MapReduce pipelines that analyse dbGaP-protected data in a manner compliant with NIH guidelines. Rail-RNA automates implementation of the protocol, making it easy for typical biomedical investigators to study protected RNA-seq data, regardless of their local IT resources or expertise.<\/jats:p>\n                  <jats:p>Availability and Implementation: Rail-RNA is available from http:\/\/rail.bio. Technical details on the Rail-dbGaP protocol as well as an implementation walkthrough are available at https:\/\/github.com\/nellore\/rail-dbgap. Detailed instructions on running Rail-RNA on dbGaP-protected data using Amazon Web Services are available at http:\/\/docs.rail.bio\/dbgap\/.<\/jats:p>\n                  <jats:p>Contacts: anellore@gmail.com or langmea@cs.jhu.edu<\/jats:p>\n                  <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btw177","type":"journal-article","created":{"date-parts":[[2016,4,28]],"date-time":"2016-04-28T12:43:00Z","timestamp":1461847380000},"page":"2551-2553","source":"Crossref","is-referenced-by-count":5,"title":["Rail-dbGaP: analyzing dbGaP-protected data in the cloud with Amazon Elastic MapReduce"],"prefix":"10.1093","volume":"32","author":[{"given":"Abhinav","family":"Nellore","sequence":"first","affiliation":[{"name":"1 Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA"},{"name":"2 Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA"},{"name":"3 Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christopher","family":"Wilks","sequence":"additional","affiliation":[{"name":"1 Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA"},{"name":"3 Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kasper D.","family":"Hansen","sequence":"additional","affiliation":[{"name":"2 Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA"},{"name":"3 Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeffrey T.","family":"Leek","sequence":"additional","affiliation":[{"name":"2 Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA"},{"name":"3 Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ben","family":"Langmead","sequence":"additional","affiliation":[{"name":"1 Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA"},{"name":"2 Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA"},{"name":"3 Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2016,4,21]]},"reference":[{"key":"2023020112584670800_btw177-B1","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1038\/ng.2653","article-title":"The genotype-tissue expression (gtex) project","volume":"45","author":"Lonsdale","year":"2013","journal-title":"Nat. Genet"},{"key":"2023020112584670800_btw177-B2","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1038\/ng1007-1181","article-title":"The ncbi dbgap database of genotypes and phenotypes","volume":"39","author":"Mailman","year":"2007","journal-title":"Nat. Genet"},{"key":"2023020112584670800_btw177-B3","volume-title":"Rail-RNA: Scalable Analysis of RNA-Seq Splicing and Coverage","author":"Nellore","year":"2015"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/32\/16\/2551\/49020696\/bioinformatics_32_16_2551.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/32\/16\/2551\/49020696\/bioinformatics_32_16_2551.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T17:58:31Z","timestamp":1675274311000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/32\/16\/2551\/1743271"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,4,21]]},"references-count":3,"journal-issue":{"issue":"16","published-print":{"date-parts":[[2016,8,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btw177","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/035287","asserted-by":"object"}]},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2016,8,15]]},"published":{"date-parts":[[2016,4,21]]}}}