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The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data
Open accessAbstract
Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
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“These results indicate that a combination of appropriate sample preparation and long reads can readily create cDNA profiles that approach the full-length sequences of mRNAs from complex samples, underlining the utility of long read platforms, despite the lower read depths they may produce37.”
From Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study (2014) · cites this paper as [37]
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Cites
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
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
The Human Genome Browser at UCSC
Kent, W. J., Sugnet, C. W., Furey, T. S., Roskin, K. M., Pringle, T. H., Zahler, A. M., & Haussler, A. D. (2002) · Genome Research · doi:10.1101/gr.229102 · Cited by 10,400
The International HapMap Project
†The International HapMap Consortium, Genotyping centres: Baylor College of Medicine and ParAllele BioScience, Gibbs, R. A., Belmont, J. W., Hardenbol, P., Willis, T. D., Yu, F., Chinese HapMap Consortium, Yang, H., Ch'ang, L.-Y., et al. (2003) · Nature · doi:10.1038/nature02168 · Cited by 6,057
Self-citationAccurate whole human genome sequencing using reversible terminator chemistry
Bentley, D. R., Balasubramanian, S., Swerdlow, H. P., Smith, G. P., Milton, J., Brown, C. G., Hall, K. P., Evers, D. J., Barnes, C. L., Bignell, H. R., et al. (2008) · Nature · doi:10.1038/nature07517 · Cited by 3,684
The complete genome of an individual by massively parallel DNA sequencing
Wheeler, D. A., Srinivasan, M., Egholm, M., Shen, Y., Chen, L., McGuire, A., He, W., Chen, Y.-J., Makhijani, V., Roth, G. T., et al. (2008) · Nature · doi:10.1038/nature06884 · Cited by 1,838
Gnirke, A., Melnikov, A., Maguire, J., Rogov, P., LeProust, E. M., Brockman, W., Fennell, T., Giannoukos, G., Fisher, S., Russ, C., et al. (2009) · Nature Biotechnology · doi:10.1038/nbt.1523 · Cited by 1,433
Self-citationHuman Genome Sequencing Using Unchained Base Reads on Self-Assembling DNA Nanoarrays
Drmanac, R., Sparks, A. B., Callow, M. J., Halpern, A. L., Burns, N. L., Kermani, B. G., Carnevali, P., Nazarenko, I., Nilsen, G. B., Yeung, G., et al. (2010) · Science · doi:10.1126/science.1181498 · Cited by 1,212
The diploid genome sequence of an Asian individual
Wang, J., Wang, W., Li, R., Li, Y., Tian, G., Goodman, L., Fan, W., Zhang, J., Li, J., Zhang, J., et al. (2008) · Nature · doi:10.1038/nature07484 · Cited by 924 · cited 1×
“This compares well against previous single individual genotyping efforts, which have seen concordance values for an individual of 86.4% and 99.6% (Wang et al. 2008; Wheeler et al. 2008).”
ResultInfluentialde Bakker, P. I. W., McVean, G., Sabeti, P. C., Miretti, M. M., Green, T., Marchini, J., Ke, X., Monsuur, A. J., Whittaker, P., Delgado, M., et al. (2006) · Nature Genetics · doi:10.1038/ng1885 · Cited by 766
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Research works printed but not linked: 17
- Bhandarkar M . 2009. Practical problem solving with hadoop and pig. In USENIX. The USENIX Association, San Diego, CA.
- 10.1038/ng.128 · DOI
- 10.1038/nmeth.1363 · DOI
- 2008, MapReduce: Simplified data processing on large clusters, Commun ACM, 51, 107, 10.1145/1327452.1327492 · DOI · Paper page
- 10.1093/bioinformatics/btp373 · DOI
- 10.1101/gr.078212.108 · DOI · Paper page
- 10.1093/bioinformatics/btn025 · DOI · Paper page
- 2005, Genome sequencing in microfabricated high-density picolitre reactors, Nature, 437, 376, 10.1038/nature03959 · DOI · Paper page
- 10.1093/bioinformatics/btp429 · DOI
- 10.1101/gr.091868.109 · DOI
- 10.1093/bioinformatics/btp450 · DOI
- 10.1101/gr.194201 · DOI · Paper page
- 10.1038/nmeth.1371 · DOI
- 10.1038/nbt1486 · DOI · Paper page
- 10.1093/nar/29.1.308 · DOI · Paper page
- 10.1016/S0168-9525(99)01751-5 · DOI
- 10.1101/gr.2188104 · DOI
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Kunkle, B. W., Carney, R. M., Kohli, M. A., Naj, A. C., Hamilton-Nelson, K. L., Whitehead, P. L., Wang, L., Lang, R., Cuccaro, M. L., Vance, J. M., et al. (2017) · Neuroscience Letters · doi:10.1016/j.neulet.2017.04.014 · Cited by 19
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Jedlickova, J., Vajter, M., Barta, T., Black, G., Mares, J., Fichtl, M., Kousal, B., Dudakova, L., & Liskova, P. (2023) · doi:10.1101/2023.02.09.23284763
Satterstrom, F. K., Kosmicki, J. A., Wang, J., Breen, M. S., De Rubeis, S., An, J.-Y., Peng, M., Collins, R., Grove, J., Klei, L., et al. (2018) · doi:10.1101/484113 · Cited by 2,323
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MethodInfluentialSelf-citation
Metadata
- Authors
- McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M., & DePristo, M. A.
- Affiliations
- Broad Institute (US)
- ORCID
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2010-07-19
- Volume
- 20
- Issue
- 9
- Pages
- 1297-1303
- ISSN
- 1088-9051 (ISSN-L)
- PMC
- PMC2928508
- OpenAlex
- W2119180969
- Cited by
- 27,895
- References
- 10
- Citations by year
- 2026: 1950 · 2025: 2502 · 2024: 2891 · 2023: 2502 · 2022: 2637 · 2021: 2797 · 2020: 2482 · 2019: 2106 · 2018: 1874 · 2017: 1655 · 2016: 1458 · 2015: 1111 · 2014: 871 · 2013: 578 · 2012: 294
- Type
- posted content
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Genome Research (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- HighWire Press Open Archive (submittedVersion)
- Funders
- Broad Institute
- National Human Genome Research Institute (U54HG003067, HG003067, 54 HG003067, U01HG005208)
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK043351)
- Topics
- 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
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genetics, Bioinformatics, and Biomedical Research
- Keywords
- GATK, MapReduce, next-generation sequencing, functional programming, shared-memory parallelism, 1000 Genomes Project, TCGA, genetic variation
- MeSH terms
- Base Sequence, Software, Genome, Sequence Analysis, DNA, Genomics
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