The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Scaling computational genomics to millions of individuals with GPUs
Open accessPublished version of a preprint
Abstract
Current genomics methods are designed to handle tens to thousands of samples but will need to scale to millions to match the pace of data and hypothesis generation in biomedical science. Here, we show that high efficiency at low cost can be achieved by leveraging general-purpose libraries for computing using graphics processing units (GPUs), such as PyTorch and TensorFlow. We demonstrate > 200-fold decreases in runtime and ~ 5–10-fold reductions in cost relative to CPUs. We anticipate that the accessibility of these libraries will lead to a widespread adoption of GPUs in computational genomics.
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Cites
LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126
Second-generation PLINK: rising to the challenge of larger and richer datasets
Chang, C. C., Chow, C. C., Tellier, L. C., Vattikuti, S., Purcell, S. M., & Lee, J. J. (2015) · Gigascience · doi:10.1186/s13742-015-0047-8 · Cited by 12,709
(2017) · Cited by 11,625
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G. S., Davis, A., Dean, J., Devin, M., et al. (2016) · arXiv · doi:10.48550/arxiv.1603.04467 · Cited by 9,408
The UK Biobank resource with deep phenotyping and genomic data
Bycroft, C., Freeman, C., Petkova, D., Band, G., Elliott, L. T., Sharp, K., Motyer, A., Vukcevic, D., Delaneau, O., O’Connell, J., et al. (2018) · Nature · doi:10.1038/s41586-018-0579-z · Cited by 8,876
Genetic effects on gene expression across human tissues
GTEx Consortium (2017) · Nature · doi:10.1038/nature24277 · Cited by 4,036
Matrix eQTL: ultra fast eQTL analysis via large matrix operations
Shabalin, A. A. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts163 · Cited by 1,694
Zhou, W., Nielsen, J. B., Fritsche, L. G., Dey, R., Gabrielsen, M. E., Wolford, B. N., LeFaive, J., VandeHaar, P., Gagliano, S. A., Gifford, A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0184-y · Cited by 1,544
Deep learning for computational biology
Angermueller, C., Pärnamaa, T., Parts, L., & Stegle, O. (2016) · Molecular Systems Biology · doi:10.15252/msb.20156651 · Cited by 1,473
Dask: Parallel Computation with Blocked algorithms and Task Scheduling
Rocklin, M. (2015) · Proceedings of the Python in Science Conference · doi:10.25080/majora-7b98e3ed-013 · Cited by 801
Research works printed but not linked: 1
- Kim J, Mouw KW, Polak P, Braunstein LZ, Kamburov A, Kwiatkowski DJ, et al. Somatic ERCC2 mutations are associated with a distinct genomic signature in urothelial tumors. Nat Genet. 2016;48:600–6 Available from: http://www.ncbi.nlm.nih.gov/pubmed/27111033 . [cited 2017 Sep 11]. · DOI · Paper page
Cited by
The GTEx Consortium atlas of genetic regulatory effects across human tissues
The GTEx Consortium, Aguet, F., Anand, S., Ardlie, K. G., Gabriel, S., Getz, G. A., Graubert, A., Hadley, K., Handsaker, R. E., Huang, K. H., et al. (2020) · Science · doi:10.1126/science.aaz1776 · Cited by 5,547
Self-citationZavidij, O., Haradhvala, N. J., Mouhieddine, T. H., Sklavenitis-Pistofidis, R., Cai, S., Reidy, M., Rahmat, M., Flaifel, A., Ferland, B., Su, N. K., et al. (2020) · Nature Cancer · doi:10.1038/s43018-020-0053-3 · Cited by 374
Self-citationLopes, K. D. P., Snijders, G. J. L., Humphrey, J., Allan, A., Sneeboer, M. A. M., Navarro, E., Schilder, B. M., Vialle, R. A., Parks, M., Missall, R., et al. (2022) · Nature Genetics · doi:10.1038/s41588-021-00976-y · Cited by 273
Humphrey, J., Venkatesh, S., Hasan, R., Herb, J. T., de Paiva Lopes, K., Küçükali, F., Byrska-Bishop, M., Evani, U. S., Narzisi, G., Fagegaltier, D., et al. (2023) · Nature Neuroscience · doi:10.1038/s41593-022-01205-3 · Cited by 138
Single-cell genomics meets human genetics
Cuomo, A. S. E., Nathan, A., Raychaudhuri, S., MacArthur, D. G., & Powell, J. E. (2023) · Nature Reviews Genetics · doi:10.1038/s41576-023-00599-5 · Cited by 124
Metadata
- Authors
- Taylor-Weiner, A., Aguet, F., Haradhvala, N. J., Gosai, S., Anand, S., Kim, J., Ardlie, K., Van Allen, E. M., & Getz, G.
- Venue
- Genome Biology
- Published
- 2019-11-01
- Volume
- 20
- Issue
- 1
- Pages
- 228-228
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- OpenAlex
- W2983859156
- Cited by
- 298
- References
- 21
- FWCI
- 11.02
- Type
- journal article
- Language
- en
- Open access
- gold
- Licence
- creativecommons.org/licenses/by/4.0/ (tdm)
- creativecommons.org/licenses/by/4.0/ (vor)
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- Taylor-Weiner, A., Aguet, F., Haradhvala, N. J., Gosai, S., Anand, S., Kim, J., Ardlie, K., Van Allen, E. M., & Getz, G. (2019). Scaling computational genomics to millions of individuals with GPUs. Genome Biology. https://doi.org/10.1186/s13059-019-1836-7
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