The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
The mutation significance cutoff: gene-level thresholds for variant predictions
Open accessAbstract
Next-generation sequencing (NGS) has made it possible to identify about 20,000 variants in the protein-coding exome of each individual, of which only a few are likely to underlie a genetic disease. Variant-level methods such as PolyPhen-2, SIFT and CADD are useful for obtaining a prediction as to whether a given variant is benign/damaging1–3 or tolerant/intolerant1–3 (we hereafter use the terms benign/deleterious). These methods are commonly interpreted in a binary manner for filtering out benign variants from NGS data, with a single significance cutoff value across all protein-coding genes. PolyPhen-2 and SIFT integrate the fixed cutoff in the software. CADD proposed (but did not recommend for categorical usage) the fixed value of 15 (or another value between 10 and 20). Gene-level methods, such as RVIS, de novo excess and GDI are also useful4–6. Combining fixed gene-level and variant-level cutoffs is also applied in the RVIS hot zone approach4. However, owing to the diversity of medical and population genetic features between human genes and across populations, a uniform cutoff is unlikely to be accurate genome-wide.
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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-citationA method and server for predicting damaging missense mutations.
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Kumar, P., Henikoff, S., & Ng, P. C. (2009) · Nature Protocols · doi:10.1038/nprot.2009.86 · Cited by 6,521
A general framework for estimating the relative pathogenicity of human genetic variants
Kircher, M., Witten, D. M., Jain, P., O'Roak, B. J., Cooper, G. M., & Shendure, J. (2014) · Nature Genetics · doi:10.1038/ng.2892 · Cited by 6,183
ClinVar: public archive of relationships among sequence variation and human phenotype
Landrum, M. J., Lee, J. M., Riley, G. R., Jang, W., Rubinstein, W. S., Church, D. M., & Maglott, D. R. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1113 · Cited by 3,516
Stenson, P. D., Mort, M., Ball, E. V., Shaw, K., Phillips, A. D., & Cooper, D. N. (2014) · Human Genetics · doi:10.1007/s00439-013-1358-4 · Cited by 1,346
Self-citationA framework for the interpretation of de novo mutation in human disease
Samocha, K. E., Robinson, E. B., Sanders, S. J., Stevens, C., Sabo, A., McGrath, L. M., Kosmicki, J. A., Rehnström, K., Mallick, S., Kirby, A., et al. (2014) · Nature Genetics · doi:10.1038/ng.3050 · Cited by 979
Genic Intolerance to Functional Variation and the Interpretation of Personal Genomes
Petrovski, S., Wang, Q., Heinzen, E. L., Allen, A. S., & Goldstein, D. B. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003709 · Cited by 901
The human gene damage index as a gene-level approach to prioritizing exome variants
Itan, Y., Shang, L., Boisson, B., Patin, E., Bolze, A., Moncada-Vélez, M., Scott, E., Ciancanelli, M. J., Lafaille, F. G., Markle, J. G., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1518646112 · Cited by 275
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Cited by
CADD: predicting the deleteriousness of variants throughout the human genome
Rentzsch, P., Witten, D., Cooper, G. M., Shendure, J., & Kircher, M. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1016 · Cited by 3,534
Early-onset autoimmunity associated with SOCS1 haploinsufficiency
Hadjadj, J., Castro, C. N., Tusseau, M., Stolzenberg, M.-C., Mazerolles, F., Aladjidi, N., Armstrong, M., Ashrafian, H., Cutcutache, I., Ebetsberger-Dachs, G., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18925-4 · Cited by 156
Human TBK1 deficiency leads to autoinflammation driven by TNF-induced cell death
Taft, J., Markson, M., Legarda, D., Patel, R., Chan, M., Malle, L., Richardson, A., Gruber, C., Martín-Fernández, M., Mancini, G. M. S., et al. (2021) · Cell · doi:10.1016/j.cell.2021.07.026 · Cited by 151
Béziat, V., Rapaport, F., Hu, J., Titeux, M., Bonnet des Claustres, M., Bourgey, M., Griffin, H., Bandet, É., Ma, C. S., Sherkat, R., et al. (2021) · Cell · doi:10.1016/j.cell.2021.06.004 · Cited by 95
Self-citationParlato, M., Charbit-Henrion, F., Hayes, P., Tiberti, A., Aloi, M., Cucchiara, S., Bègue, B., Bras, M., Pouliet, A., Rakotobe, S., et al. (2017) · Gastroenterology · doi:10.1053/j.gastro.2016.12.053 · Cited by 58
Metadata
- Authors
- Itan, Y., Shang, L., Boisson, B., Ciancanelli, M. J., Markle, J. G., Martinez-Barricarte, R., Scott, E., Shah, I., Stenson, P. D., Gleeson, J., Cooper, D. N., Quintana-Murci, L., Zhang, S.-Y., Abel, L., & Casanova, J.-L.
- Venue
- Nature Methods
- Published
- 2016-01-28
- Volume
- 13
- Issue
- 2
- Pages
- 109-110
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W2255312347
- Cited by
- 328
- References
- 9
- FWCI
- 23.97
- Type
- journal article
- Language
- en
- Open access
- green
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- Itan, Y., Shang, L., Boisson, B., Ciancanelli, M. J., Markle, J. G., Martinez-Barricarte, R., Scott, E., Shah, I., Stenson, P. D., Gleeson, J., Cooper, D. N., Quintana-Murci, L., Zhang, S.-Y., Abel, L., & Casanova, J.-L. (2016). The mutation significance cutoff: gene-level thresholds for variant predictions. Nature Methods. https://doi.org/10.1038/nmeth.3739
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