The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Human genetic variation database, a reference database of genetic variations in the Japanese population
Open accessAbstract
Whole-genome and -exome resequencing using next-generation sequencers is a powerful approach for identifying genomic variations that are associated with diseases. However, systematic strategies for prioritizing causative variants from many candidates to explain the disease phenotype are still far from being established, because the population-specific frequency spectrum of genetic variation has not been characterized. Here, we have collected exomic genetic variation from 1208 Japanese individuals through a collaborative effort, and aggregated the data into a prevailing catalog. In total, we identified 156 622 previously unreported variants. The allele frequencies for the majority (88.8%) were lower than 0.5% in allele frequency and predicted to be functionally deleterious. In addition, we have constructed a Japanese-specific major allele reference genome by which the number of unique mapping of the short reads in our data has increased 0.045% on average. Our results illustrate the importance of constructing an ethnicity-specific reference genome for identifying rare variants. All the collected data were centralized to a newly developed database to serve as useful resources for exploring pathogenic variations. Public access to the database is available at http://www.genome.med.kyoto-u.ac.jp/SnpDB/.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
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
KEGG: Kyoto Encyclopedia of Genes and Genomes
Kanehisa, M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.27 · Cited by 37,077
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
KEGG: Kyoto Encyclopedia of Genes and Genomes
Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.1.29 · Cited by 31,232
Initial sequencing and analysis of the human genome
International Human Genome Sequencing Consortium, Whitehead Institute for Biomedical Research, C. F. G. R., Lander, E. S., Linton, L. M., Birren, B., Nusbaum, C., Zody, M. C., Baldwin, J., Devon, K., Dewar, K., et al. (2001) · Nature · doi:10.1038/35057062 · Cited by 24,216
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
Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.
Tajima, F. (1989) · Genetics · doi:10.1093/genetics/123.3.585 · Cited by 13,941
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
A framework for variation discovery and genotyping using next-generation DNA sequencing data
DePristo, M. A., Banks, E., Poplin, R., Garimella, K. V., Maguire, J. R., Hartl, C., Philippakis, A. A., del Angel, G., Rivas, M. A., Hanna, M., et al. (2011) · Nature Genetics · doi:10.1038/ng.806 · Cited by 11,456
Cited by
Seino, T., Kawasaki, S., Shimokawa, M., Tamagawa, H., Toshimitsu, K., Fujii, M., Ohta, Y., Matano, M., Nanki, K., Kawasaki, K., et al. (2018) · Cell Stem Cell · doi:10.1016/j.stem.2017.12.009 · Cited by 631
Genomic characterization of biliary tract cancers identifies driver genes and predisposing mutations
Wardell, C. P., Fujita, M., Yamada, T., Simbolo, M., Fassan, M., Karlic, R., Polak, P., Kim, J., Hatanaka, Y., Maejima, K., et al. (2018) · Journal of Hepatology · doi:10.1016/j.jhep.2018.01.009 · Cited by 373
An Organoid Biobank of Neuroendocrine Neoplasms Enables Genotype-Phenotype Mapping
Kawasaki, K., Toshimitsu, K., Matano, M., Fujita, M., Fujii, M., Togasaki, K., Ebisudani, T., Shimokawa, M., Takano, A., Takahashi, S., et al. (2020) · Cell · doi:10.1016/j.cell.2020.10.023 · Cited by 238
Nanki, Y., Chiyoda, T., Hirasawa, A., Ookubo, A., Itoh, M., Ueno, M., Akahane, T., Kameyama, K., Yamagami, W., Kataoka, F., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-69488-9 · Cited by 165
Yamada, S., Honzawa, Y., Yamamoto, S., Matsuura, M., Kitamoto, H., Okabe, M., Kakiuchi, N., Toyonaga, T., Kobayashi, T., Hibi, T., et al. (2024) · Inflammatory Bowel Diseases · doi:10.1093/ibd/izad259 · Cited by 8
Metadata
- Authors
- Higasa, K., Miyake, N., Yoshimura, J., Okamura, K., Niihori, T., Saitsu, H., Doi, K., Shimizu, M., Nakabayashi, K., Aoki, Y., Tsurusaki, Y., Morishita, S., Kawaguchi, T., Migita, O., Nakayama, K., Nakashima, M., Mitsui, J., Narahara, M., Hayashi, K., Funayama, R., Yamaguchi, D., Ishiura, H., Ko, W.-Y., Hata, K., Nagashima, T., Yamada, R., Matsubara, Y., Umezawa, A., Tsuji, S., Matsumoto, N., & Matsuda, F.
- Venue
- Journal of Human Genetics
- Published
- 2016-02-25
- Volume
- 61
- Issue
- 6
- Pages
- 547-553
- ISSN
- 1434-5161 (ISSN-L)
- 1435-232X
- OpenAlex
- W2278487942
- Cited by
- 304
- References
- 46
- FWCI
- 33.02
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Human genetic variation database, a reference database of genetic variations in the Japanese population. https://app.cochat.ai/papers/10.1038/jhg.2016.12
- The paper
- Higasa, K., Miyake, N., Yoshimura, J., Okamura, K., Niihori, T., Saitsu, H., Doi, K., Shimizu, M., Nakabayashi, K., Aoki, Y., Tsurusaki, Y., Morishita, S., Kawaguchi, T., Migita, O., Nakayama, K., Nakashima, M., Mitsui, J., Narahara, M., Hayashi, K., . . . Matsuda, F. (2016). Human genetic variation database, a reference database of genetic variations in the Japanese population. Journal of Human Genetics. https://doi.org/10.1038/jhg.2016.12
Data sources
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.
