The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Evaluating the evaluation of cancer driver genes
Open accessAbstract
Significance: Modern large-scale sequencing of human cancers seeks to comprehensively discover mutated genes that confer a selective advantage to cancer cells. Key to this effort has been development of computational algorithms to find genes that drive cancer based on their patterns of mutation in large patient cohorts. Because there is no generally accepted gold standard of driver genes, it has been difficult to quantitatively compare these methods. We present a machine-learning–based method for driver gene prediction and a protocol to evaluate and compare prediction methods. Our results suggest that most current methods do not adequately account for heterogeneity in the number of mutations expected by chance and consequently yield many false-positive calls, particularly in cancers with high mutation rate.
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Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
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
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692
Signatures of mutational processes in human cancer
Initiative, A. P. C. G., Alexandrov, L. B., ICGC Breast Cancer Consortium, ICGC MMML-Seq Consortium, PedBrain, I., Nik-Zainal, S., Wedge, D. C., Aparicio, S. A. J. R., Behjati, S., Biankin, A. V., et al. (2013) · Nature · doi:10.1038/nature12477 · Cited by 9,660
Vogelstein, B., Papadopoulos, N., Velculescu, V. E., Zhou, S., Diaz, L. A., & Kinzler, K. W. (2013) · Science · doi:10.1126/science.1235122 · Cited by 7,863
Self-citationMutational heterogeneity in cancer and the search for new cancer-associated genes
Lawrence, M. S., Stojanov, P., Polak, P., Kryukov, G. V., Cibulskis, K., Sivachenko, A., Carter, S. L., Stewart, C., Mermel, C. H., Roberts, S. A., et al. (2013) · Nature · doi:10.1038/nature12213 · Cited by 5,461
Neural Networks and the Bias/Variance Dilemma
Geman, S., Bienenstock, E., & Doursat, R. (1992) · Neural Computation · doi:10.1162/neco.1992.4.1.1 · Cited by 3,578
A census of human cancer genes
Futreal, P. A., Coin, L., Marshall, M., Down, T., Hubbard, T., Wooster, R., Rahman, N., & Stratton, M. R. (2004) · Nature Reviews Cancer · doi:10.1038/nrc1299 · Cited by 3,184
The Consensus Coding Sequences of Human Breast and Colorectal Cancers
Sjöblom, T., Jones, S., Wood, L. D., Parsons, D. W., Lin, J., Barber, T. D., Mandelker, D., Leary, R. J., Ptak, J., Silliman, N., et al. (2006) · Science · doi:10.1126/science.1133427 · Cited by 3,169
Self-citationDiscovery and saturation analysis of cancer genes across 21 tumour types
Lawrence, M. S., Stojanov, P., Mermel, C. H., Robinson, J. T., Garraway, L. A., Golub, T. R., Meyerson, M., Gabriel, S. B., Lander, E. S., & Getz, G. (2014) · Nature · doi:10.1038/nature12912 · Cited by 3,096
Cited by
Comprehensive Characterization of Cancer Driver Genes and Mutations
Bailey, M. H., Tokheim, C., Porta-Pardo, E., Sengupta, S., Bertrand, D., Weerasinghe, A., Colaprico, A., Wendl, M. C., Kim, J., Reardon, B., et al. (2018) · Cell · doi:10.1016/j.cell.2018.02.060 · Cited by 2,256
Self-citationA compendium of mutational cancer driver genes
Martínez-Jiménez, F., Muiños, F., Sentís, I., Deu-Pons, J., Reyes-Salazar, I., Arnedo-Pac, C., Mularoni, L., Pich, O., Bonet, J., Kranas, H., et al. (2020) · Nature Reviews Cancer · doi:10.1038/s41568-020-0290-x · Cited by 1,296
Perspective 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-citationSeiler, M., Peng, S., Agrawal, A. A., Palacino, J., Teng, T., Zhu, P., Smith, P. G., Caesar-Johnson, S. J., Demchok, J. A., Felau, I., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.01.088 · Cited by 444
Billon, P., Bryant, E. E., Joseph, S. A., Nambiar, T. S., Hayward, S. B., Rothstein, R., & Ciccia, A. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.08.008 · Cited by 363
Metadata
- Authors
- Tokheim, C. J., Papadopoulos, N., Kinzler, K. W., Vogelstein, B., & Karchin, R.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2016-11-22
- Volume
- 113
- Issue
- 50
- Pages
- 14330-14335
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2557187647
- Cited by
- 384
- References
- 39
- FWCI
- 13.47
- Type
- journal article
- Language
- en
- Open access
- green
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