The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
SomaticSniper: identification of somatic point mutations in whole genome sequencing data
Open accessAbstract
Motivation: The sequencing of tumors and their matched normals is frequently used to study the genetic composition of cancer. Despite this fact, there remains a dearth of available software tools designed to compare sequences in pairs of samples and identify sites that are likely to be unique to one sample. Results: In this article, we describe the mathematical basis of our SomaticSniper software for comparing tumor and normal pairs. We estimate its sensitivity and precision, and present several common sources of error resulting in miscalls. Availability and implementation: Binaries are freely available for download at http://gmt.genome.wustl.edu/somatic-sniper/current/, implemented in C and supported on Linux and Mac OS X. Contact: delarson@wustl.edu; lding@wustl.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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
Recurring mutations found by sequencing an acute myeloid leukemia genome
Mardis, E. R., Ding, L., Dooling, D. J., Larson, D. E., McLellan, M. D., Chen, K., Koboldt, D. C., Fulton, R. S., Delehaunty, K. D., McGrath, S. D., et al. (2009) · New England Journal of Medicine · doi:10.1056/nejmoa0903840 · Cited by 2,219
Self-citationDNMT3A Mutations in Acute Myeloid Leukemia
Ley, T. J., Ding, L., Walter, M. J., McLellan, M. D., Lamprecht, T., Larson, D. E., Kandoth, C., Payton, J. E., Baty, J., Welch, J., et al. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa1005143 · Cited by 1,983
Self-citationARID1A Mutations in Endometriosis-Associated Ovarian Carcinomas
Wiegand, K. C., Shah, S. P., Al-Agha, O. M., Zhao, Y., Tse, K., Zeng, T., Senz, J., McConechy, M. K., Anglesio, M. S., Kalloger, S. E., et al. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa1008433 · Cited by 1,712
A comprehensive catalogue of somatic mutations from a human cancer genome
Pleasance, E. D., Cheetham, R. K., Stephens, P. J., McBride, D. J., Humphray, S. J., Greenman, C. D., Varela, I., Lin, M.-L., Ordóñez, G. R., Bignell, G. R., et al. (2010) · Nature · doi:10.1038/nature08658 · Cited by 1,696
SNP detection for massively parallel whole-genome resequencing
Li, R., Li, Y., Fang, X., Yang, H., Wang, J., Kristiansen, K., & Wang, J. (2009) · Genome Research · doi:10.1101/gr.088013.108 · Cited by 944
Research works printed but not linked: 15
- Carvalho, 2010, Quantifying uncertainty in genotype calls, Bioinformatics, 26, 242, 10.1093/bioinformatics/btp624 · DOI
- Ding, 2010, Genome remodelling in a basal-like breast cancer metastasis and xenograft, Nature, 464, 999, 10.1038/nature08989 · DOI · Paper page
- Forbes, 2011, COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer, Nucleic Acids Res., 39, D945, 10.1093/nar/gkq929 · DOI · Paper page
- Goya, 2010, SNVMix: predicting single nucleotide variants from next-generation sequencing of tumors, Bioinformatics, 26, 730, 10.1093/bioinformatics/btq040 · DOI
- Greenman, 2007, Patterns of somatic mutation in human cancer genomes, Nature, 446, 153, 10.1038/nature05610 · DOI · Paper page
- Jones, 2010, Frequent mutations of chromatin remodeling gene ARID1A in ovarian clear cell carcinoma, Science, 330, 228, 10.1126/science.1196333 · DOI · Paper page
- Koboldt, 2009, VarScan: variant detection in massively parallel sequencing of individual and pooled samples, Bioinformatics, 25, 2283, 10.1093/bioinformatics/btp373 · DOI · Paper page
- Ley, 2008, DNA sequencing of a cytogenetically normal acute myeloid leukaemia genome, Nature, 456, 66, 10.1038/nature07485 · DOI · Paper page
- Li, 2008, Mapping short DNA sequencing reads and calling variants using mapping quality scores, Genome Res., 18, 1851, 10.1101/gr.078212.108 · DOI · Paper page
- Pleasance, 2010, A small-cell lung cancer genome with complex signatures of tobacco exposure, Nature, 463, 184, 10.1038/nature08629 · DOI · Paper page
- Shah, 2009, Mutation of FOXL2 in granulosa-cell tumors of the ovary, N. Engl. J. Med., 360, 2719, 10.1056/NEJMoa0902542 · DOI · Paper page
- Shah, 2009, Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution, Nature, 461, 809, 10.1038/nature08489 · DOI · Paper page
- Sherry, 2001, dbSNP: the NCBI database of genetic variation, Nucleic Acids Res., 29, 308, 10.1093/nar/29.1.308 · DOI · Paper page
- Wendl, 2008, Aspects of coverage in medical DNA sequencing, BMC Bioinformatics, 9, 239, 10.1186/1471-2105-9-239 · DOI
- Zhang, 2002, Beta approximation to the distribution of Kolmogorov-Smirnov statistic, Ann. Ins. Stat. Math., 54, 577, 10.1023/A:1022463111224 · doi:10.1023/a:1022463111224
Cited by
Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer
Rizvi, N. A., Hellmann, M. D., Snyder, A., Kvistborg, P., Makarov, V., Havel, J. J., Lee, W., Yuan, J., Wong, P., Ho, T. S., et al. (2015) · Science · doi:10.1126/science.aaa1348 · Cited by 7,802
Mutational landscape and significance across 12 major cancer types
Kandoth, C., McLellan, M. D., Vandin, F., Ye, K., Niu, B., Lu, C., Xie, M., Zhang, Q., McMichael, J. F., Wyczalkowski, M. A., et al. (2013) · Nature · doi:10.1038/nature12634 · Cited by 4,419
Self-citationTumor and Microenvironment Evolution during Immunotherapy with Nivolumab
Riaz, N., Havel, J. J., Makarov, V., Desrichard, A., Urba, W. J., Sims, J. S., Hodi, F. S., Martín-Algarra, S., Mandal, R., Sharfman, W. H., et al. (2017) · Cell · doi:10.1016/j.cell.2017.09.028 · Cited by 2,401
Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing
Ding, L., Ley, T. J., Larson, D. E., Miller, C. A., Koboldt, D. C., Welch, J. S., Ritchey, J. K., Young, M. A., Lamprecht, T., McLellan, M. D., et al. (2012) · Nature · doi:10.1038/nature10738 · Cited by 1,993
The origin and evolution of mutations in acute myeloid leukemia
Welch, J. S., Ley, T. J., Link, D. C., Miller, C. A., Larson, D. E., Koboldt, D. C., Wartman, L. D., Lamprecht, T. L., Liu, F., Xia, J., et al. (2012) · Cell · doi:10.1016/j.cell.2012.06.023 · Cited by 1,575
Self-citationPatient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy
Chowell, D., Morris, L. G. T., Grigg, C. M., Weber, J. K., Samstein, R. M., Makarov, V., Kuo, F., Kendall, S. M., Requena, D., Riaz, N., et al. (2018) · Science · doi:10.1126/science.aao4572 · Cited by 1,142
Dijkstra, K. K., Cattaneo, C. M., Weeber, F., Chalabi, M., van de Haar, J., Fanchi, L. F., Slagter, M., van der Velden, D. L., Kaing, S., Kelderman, S., et al. (2018) · Cell · doi:10.1016/j.cell.2018.07.009 · Cited by 1,135
Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas
Abeshouse, A., Adebamowo, C., Adebamowo, S. N., Akbani, R., Akeredolu, T., Ally, A., Anderson, M. L., Anur, P., Appelbaum, E. L., Armenia, J., et al. (2017) · Cell · doi:10.1016/j.cell.2017.10.014 · Cited by 1,069
Self-citationThe cohesin release factor WAPL restricts chromatin loop extension
Haarhuis, J. H. I., van der Weide, R. H., Blomen, V. A., Yáñez-Cuna, J. O., Amendola, M., van Ruiten, M. S., Krijger, P. H. L., Teunissen, H., Medema, R. H., van Steensel, B., et al. (2017) · Cell · doi:10.1016/j.cell.2017.04.013 · Cited by 793
Role of TP53 mutations in the origin and evolution of therapy-related acute myeloid leukaemia
Wong, T. N., Ramsingh, G., Young, A. L., Miller, C. A., Touma, W., Welch, J. S., Lamprecht, T. L., Shen, D., Hundal, J., Fulton, R. S., et al. (2015) · Nature · doi:10.1038/nature13968 · Cited by 892
Self-citationPerspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics
Ding, L., Bailey, M. H., Porta-Pardo, E., Thorsson, V., Colaprico, A., Bertrand, D., Gibbs, D. L., Weerasinghe, A., Huang, K.-L., Tokheim, C., et al. (2018) · Cell · doi:10.1016/j.cell.2018.03.033 · Cited by 399
Self-citationClonal diversity of recurrently mutated genes in myelodysplastic syndromes
Walter, M. J., Shen, D., Shao, J., Ding, L., White, B. S., Kandoth, C., Miller, C. A., Niu, B., McLellan, M. D., Dees, N. D., et al. (2013) · Leukemia · doi:10.1038/leu.2013.58 · Cited by 284
Self-citationUltraviolet radiation accelerates BRAF-driven melanomagenesis by targeting TP53
Viros, A., Sanchez-Laorden, B., Pedersen, M., Furney, S. J., Rae, J., Hogan, K., Ejiama, S., Girotti, M. R., Cook, M., Dhomen, N., et al. (2014) · Nature · doi:10.1038/nature13298 · Cited by 249
A general approach for detecting expressed mutations in AML cells using single cell RNA-sequencing
Petti, A. A., Williams, S. R., Miller, C. A., Fiddes, I. T., Srivatsan, S. N., Chen, D. Y., Fronick, C. C., Fulton, R. S., Church, D. M., & Ley, T. J. (2019) · Nature Communications · doi:10.1038/s41467-019-11591-1 · Cited by 215
Self-citationXu, Y., Su, G.-H., Ma, D., Xiao, Y., Shao, Z.-M., & Jiang, Y.-Z. (2021) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-021-00729-7 · Cited by 163
Ooi, A., Dykema, K., Ansari, A., Petillo, D., Snider, J., Kahnoski, R., Anema, J., Craig, D., Carpten, J., Teh, B.-T., et al. (2013) · Cancer Research · doi:10.1158/0008-5472.can-12-3227 · Cited by 159
Landmarks of human embryonic development inscribed in somatic mutations
Bizzotto, S., Dou, Y., Ganz, J., Doan, R. N., Kwon, M., Bohrson, C. L., Kim, S. N., Bae, T., Abyzov, A., NIMH Brain Somatic Mosaicism Network, et al. (2021) · Science · doi:10.1126/science.abe1544 · Cited by 117
Cole, C. B., Russler-Germain, D. A., Ketkar, S., Verdoni, A. M., Smith, A. M., Bangert, C. V., Helton, N. M., Guo, M., Klco, J. M., O’Laughlin, S., et al. (2017) · Journal of Clinical Investigation · doi:10.1172/jci93041 · Cited by 84
Self-citationVision transformer-based weakly supervised histopathological image analysis of primary brain tumors
Li, Z., Cong, Y., Chen, X., Qi, J., Sun, J., Yan, T., Yang, H., Liu, J., Lu, E., Wang, L., et al. (2023) · iScience · doi:10.1016/j.isci.2022.105872 · Cited by 82
Accelerating genomic workflows using NVIDIA Parabricks
O’Connell, K. A., Yosufzai, Z. B., Campbell, R. A., Lobb, C. J., Engelken, H. T., Gorrell, L. M., Carlson, T. B., Catana, J. J., Mikdadi, D., Bonazzi, V. R., et al. (2023) · BMC Bioinformatics · doi:10.1186/s12859-023-05292-2 · Cited by 62
Zhang, B., & Bassani-Sternberg, M. (2023) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2023-007073 · Cited by 44
Sahraeian, S. M. E., Fang, L. T., Karagiannis, K., Moos, M., Smith, S., Santana-Quintero, L., Xiao, C., Colgan, M., Hong, H., Mohiyuddin, M., et al. (2022) · Genome biology · doi:10.1186/s13059-021-02592-9 · Cited by 27
Transformers meets neoantigen detection: a systematic literature review
Machaca, V., Goyzueta, V., Cruz, M. G., Sejje, E., Pilco, L. M., López, J., & Túpac, Y. (2024) · Journal of Integrative Bioinformatics · doi:10.1515/jib-2023-0043 · Cited by 5
Metadata
- Authors
- Larson, D. E., Harris, C. C., Chen, K., Koboldt, D. C., Abbott, T. E., Dooling, D. J., Ley, T. J., Mardis, E. R., Wilson, R. K., & Ding, L.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-12-06
- Volume
- 28
- Issue
- 3
- Pages
- 311-317
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2151794156
- Cited by
- 661
- References
- 6
- FWCI
- 10.89
- Type
- journal article
- Language
- en
- Open access
- bronze
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
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.
