The sequence read archive: explosive growth of sequencing data
Open accessAbstract
New generation sequencing platforms are producing data with significantly higher throughput and lower cost. A portion of this capacity is devoted to individual and community scientific projects. As these projects reach publication, raw sequencing datasets are submitted into the primary next-generation sequence data archive, the Sequence Read Archive (SRA). Archiving experimental data is the key to the progress of reproducible science. The SRA was established as a public repository for next-generation sequence data as a part of the International Nucleotide Sequence Database Collaboration (INSDC). INSDC is composed of the National Center for Biotechnology Information (NCBI), the European Bioinformatics Institute (EBI) and the DNA Data Bank of Japan (DDBJ). The SRA is accessible at www.ncbi.nlm.nih.gov/sra from NCBI, at www.ebi.ac.uk/ena from EBI and at trace.ddbj.nig.ac.jp from DDBJ. In this article, we present the content and structure of the SRA and report on updated metadata structures, submission file formats and supported sequencing platforms. We also briefly outline our various responses to the challenge of explosive data growth.
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We validated stop codon mutations, splice site mutations, and frameshifting insertions/deletions with unassembled sequencing reads stored in the sequence read archive (SRA) or the NCBI trace archive.
“we validated stop codon mutations, splice site mutations, and frameshifting insertions/deletions with unassembled sequencing reads stored in the sequence read archive (SRA)65 or the NCBI trace archive.”
From A genomics approach reveals insights into the importance of gene losses for mammalian adaptations (2018) · cites this paper as [65]
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The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041 · see citing works
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Research works printed but not linked: 7
- [1]Shumway M Cochrane G Sugawara H Archiving next generation sequencing data Nucleic Acids Res. 2010 38 D870 D871 19965774 PMC2808927
- [2]Leinonen R Sugawara H Shumway M The sequence read archive Nucleic Acids Res. 2011 39 D19 D21 21062823 PMC3013647
- [3]Karsch-Mizrachi I Nakamura Y Cochrane G The International Nucleotide Sequence Database Collaboration Nucleic Acids Res 2012 40 D33 D37 22080546 PMC3244996
- [5]Barrett T Troup DB Wilhite SE Ledoux P Evangelista C Kim IF Tomashevsky M Marshall KA Phillippy KH Sherman PM NCBI GEO: archive for functional genomics data sets–10 years on Nucleic Acids Res. 2011 39 D1005 D1010 21097893 PMC3013736
- [6]Parkinson H Sarkans U Kolesnikov N Abeygunawardena N Burdett T Dylag M Emam I Farne A Hastings E Holloway E ArrayExpress update–an archive of microarray and high-throughput sequencing-based functional genomics experiments Nucleic Acids Res. 2011 39 D1002 D1004 21071405 PMC3013660
- [7]Kodama Y Mashima J Kaminuma E Gojobori T Ogasawara O Takagi T Okubo K Nakamura Y The DNA Data Bank of Japan launches a new resource DDBJ Omics Archive of functional genomics experiments Nucleic Acids Res. in press PMC3244990 22110025
- [8]Fritz MH-Y Leinonen R Cochrane G Birney E Efficient storage of high throughput DNA sequencing data using reference-based compression Genome Res. 2011 21 734 740 21245279 PMC3083090
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- Authors
- Kodama, Y., Shumway, M., Leinonen, R., & on behalf of the International Nucleotide Sequence Database Collaboration
- Affiliations
- National Institute of Genetics (JP)
- Corresponding author
- Kodama, Y.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-10-18
- Volume
- 40
- Issue
- D1
- Pages
- D54-D56
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC3245110
- OpenAlex
- W2165446840
- Cited by
- 894
- References
- 1
- Citations by year
- 2026: 45 · 2025: 40 · 2024: 50 · 2023: 56 · 2022: 81 · 2021: 100 · 2020: 67 · 2019: 74 · 2018: 68 · 2017: 84 · 2016: 60 · 2015: 62 · 2014: 39 · 2013: 49 · 2012: 16
- FWCI
- 92.98
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- Wellcome Trust (085532)
- European Molecular Biology Laboratory
- European Commission
- Ministry of Education, Culture, Sports, Science and Technology
- National Institutes of Health
- U.S. National Library of Medicine
- Topics
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
- Keywords
- Sequence Read Archive, next-generation sequencing data, data volume growth, metadata structure, sequencing platforms, reproducible science, INSDC, NCBI, EBI, DDBJ
- MeSH terms
- Internet, Genomics, Databases, Nucleic Acid, High-Throughput Nucleotide Sequencing
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