The DOI matches its Crossref record; 90 of the 90 references it cites were found in a registry or an index.
Ensembl variation resources
Open accessAbstract
The major goal of sequencing humans and many other species is to understand the link between genomic variation, phenotype and disease. There are numerous valuable and well-established variation resources, but collating and making sense of non-homogeneous, often large-scale data sets from disparate sources remains a challenge. Without a systematic catalogue of these data and appropriate query and annotation tools, understanding the genome sequence of an individual and assessing their disease risk is impossible. In Ensembl, we substantially solve this problem: we develop methods to facilitate data integration and broad access; aggregate information in a consistent manner and make it available a variety of standard formats, both visually and programmatically; build analysis pipelines to compare variants to comprehensive genomic annotation sets; and make all tools and data publicly available.
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Citations
Cites
Richards, S., Aziz, N., Bale, S., Bick, D., Das, S., Gastier-Foster, J., Grody, W. W., Hegde, M., Lyon, E., Spector, E., et al. (2015) · Genetics in Medicine · doi:10.1038/gim.2015.30 · Cited by 32,594
A global reference for human genetic variation
The 1000 Genomes Project Consortium, authors, C., Auton, A., Abecasis, G. R., Steering committee, Altshuler, D. M., Durbin, R. M., Abecasis, G. R., Bentley, D. R., Chakravarti, A., et al. (2015) · Nature · doi:10.1038/nature15393 · Cited by 18,247
Self-citationThe variant call format and VCFtools
Danecek, P., Auton, A., Abecasis, G., Albers, C. A., Banks, E., DePristo, M. A., Handsaker, R. E., Lunter, G., Marth, G. T., Sherry, S. T., et al. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr330 · Cited by 16,200
Haploview: analysis and visualization of LD and haplotype maps
Barrett, J. C., Fry, B., Maller, J., & Daly, M. J. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bth457 · Cited by 14,525
A method and server for predicting damaging missense mutations.
Adzhubei, I. A., Schmidt, S., Peshkin, L., Ramensky, V. E., Gerasimova, A., Bork, P., Kondrashov, A. S., & Sunyaev, S. R. (2010) · Nature Methods · doi:10.1038/nmeth0410-248 · Cited by 13,194
Database resources of the National Center for Biotechnology Information: update
Wheeler, D. L. (2004) · Nucleic Acids Research · doi:10.1093/nar/gkh073 · Cited by 10,641
Analysis of protein-coding genetic variation in 60,706 humans
Exome Aggregation Consortium, Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., O’Donnell-Luria, A. H., Ware, J. S., Hill, A. J., et al. (2016) · Nature · doi:10.1038/nature19057 · Cited by 9,587
Shrestha, S., & Offer, S. M. (2016) · Medical Epigenetics · doi:10.1159/000444713 · Cited by 8,914
The Ensembl Variant Effect Predictor
McLaren, W., Gil, L., Hunt, S. E., Riat, H. S., Ritchie, G. R. S., Thormann, A., Flicek, P., & Cunningham, F. (2016) · Genome Biology · doi:10.1186/s13059-016-0974-4 · Cited by 8,099
Self-citationdbSNP: the NCBI database of genetic variation
Sherry, S. T. (2001) · Nucleic Acids Research · doi:10.1093/nar/29.1.308 · Cited by 7,502
Cited by
Raudvere, U., Kolberg, L., Kuzmin, I., Arak, T., Adler, P., Peterson, H., & Vilo, J. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz369 · Cited by 5,045
Yang, J., Hirai, Y., Iida, K., Ito, S., Trumm, M., Terada, S., Sakai, R., Tsuchiya, T., Tabata, O., & Kamei, K.-I. (2020) · doi:10.1101/2020.06.10.141606 · Cited by 110
Yang, J., Hirai, Y., Iida, K., Ito, S., Trumm, M., Terada, S., Sakai, R., Tsuchiya, T., Tabata, O., & Kamei, K.-I. (2023) · Communications Biology · doi:10.1038/s42003-023-04710-8 · Cited by 98
Pekmezovic, M., Hovhannisyan, H., Gresnigt, M. S., Iracane, E., Oliveira-Pacheco, J., Siscar-Lewin, S., Seemann, E., Qualmann, B., Kalkreuter, T., Müller, S., et al. (2021) · Nature Microbiology · doi:10.1038/s41564-021-00875-2 · Cited by 96
Jagoda, E., Xue, J. R., Reilly, S. K., Dannemann, M., Racimo, F., Huerta-Sanchez, E., Sankararaman, S., Kelso, J., Pagani, L., Sabeti, P. C., et al. (2022) · Molecular Biology and Evolution · doi:10.1093/molbev/msab304 · Cited by 47
Metadata
- Authors
- Hunt, S. E., McLaren, W., Gil, L., Thormann, A., Schuilenburg, H., Sheppard, D., Parton, A., Armean, I. M., Trevanion, S. J., Flicek, P., & Cunningham, F.
- Venue
- Database
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-01-01
- Volume
- 2018
- ISSN
- 1758-0463 (ISSN-L)
- OpenAlex
- W2911561283
- Cited by
- 452
- References
- 90
- FWCI
- 38.45
- Type
- journal article
- Language
- en
- Open access
- gold
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- CoChat. (2026). Citation check: Ensembl variation resources. https://app.cochat.ai/papers/10.1093/database/bay119
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- Hunt, S. E., McLaren, W., Gil, L., Thormann, A., Schuilenburg, H., Sheppard, D., Parton, A., Armean, I. M., Trevanion, S. J., Flicek, P., & Cunningham, F. (2018). Ensembl variation resources. Database. https://doi.org/10.1093/database/bay119
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
