The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
MuSiC: Identifying mutational significance in cancer genomes
Open accessAbstract
Massively parallel sequencing technology and the associated rapidly decreasing sequencing costs have enabled systemic analyses of somatic mutations in large cohorts of cancer cases. Here we introduce a comprehensive mutational analysis pipeline that uses standardized sequence-based inputs along with multiple types of clinical data to establish correlations among mutation sites, affected genes and pathways, and to ultimately separate the commonly abundant passenger mutations from the truly significant events. In other words, we aim to determine the Mu tational S ignificance i n C ancer (MuSiC) for these large data sets. The integration of analytical operations in the MuSiC framework is widely applicable to a broad set of tumor types and offers the benefits of automation as well as standardization. Herein, we describe the computational structure and statistical underpinnings of the MuSiC pipeline and demonstrate its performance using 316 ovarian cancer samples from the TCGA ovarian cancer project. MuSiC correctly confirms many expected results, and identifies several potentially novel avenues for discovery.
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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
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
Kumar, P., Henikoff, S., & Ng, P. C. (2009) · Nature Protocols · doi:10.1038/nprot.2009.86 · Cited by 6,521
The Pfam protein families database
Finn, R. D., Mistry, J., Tate, J., Coggill, P., Heger, A., Pollington, J. E., Gavin, O. L., Gunasekaran, P., Ceric, G., Forslund, K., et al. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkp985 · Cited by 2,694
Somatic mutations affect key pathways in lung adenocarcinoma
Ding, L., Getz, G., Wheeler, D. A., Mardis, E. R., McLellan, M. D., Cibulskis, K., Sougnez, C., Greulich, H., Muzny, D. M., Morgan, M. B., et al. (2008) · Nature · doi:10.1038/nature07423 · Cited by 2,681
Self-citationA novel signaling pathway impact analysis
Tarca, A. L., Draghici, S., Khatri, P., Hassan, S. S., Mittal, P., Kim, J.-S., Kim, C. J., Kusanovic, J. P., & Romero, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btn577 · Cited by 1,031
Vaske, C. J., Benz, S. C., Sanborn, J. Z., Earl, D., Szeto, C., Zhu, J., Haussler, D., & Stuart, J. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq182 · Cited by 786
Cited by
Comprehensive molecular portraits of human breast tumours
The Cancer Genome Atlas Network (2012) · Nature · doi:10.1038/nature11412 · Cited by 12,129
Inferring tumour purity and stromal and immune cell admixture from expression data
Yoshihara, K., Shahmoradgoli, M., Martínez, E., Vegesna, R., Kim, H., Torres-Garcia, W., Treviño, V., Shen, H., Laird, P. W., Levine, D. A., et al. (2013) · Nature Communications · doi:10.1038/ncomms3612 · Cited by 9,778
Genomic and Epigenomic Landscapes of Adult De Novo Acute Myeloid Leukemia
The Cancer Genome Atlas Research Network (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1301689 · Cited by 5,078
Maftools: efficient and comprehensive analysis of somatic variants in cancer
Mayakonda, A., Lin, D.-C., Assenov, Y., Plass, C., & Koeffler, H. P. (2018) · Genome Research · doi:10.1101/gr.239244.118 · Cited by 4,935
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
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Metadata
- Authors
- Dees, N. D., Zhang, Q., Kandoth, C., Wendl, M. C., Schierding, W., Koboldt, D. C., Mooney, T. B., Callaway, M. B., Dooling, D., Mardis, E. R., Wilson, R. K., & Ding, L.
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2012-07-03
- Volume
- 22
- Issue
- 8
- Pages
- 1589-1598
- ISSN
- 1088-9051 (ISSN-L)
- OpenAlex
- W2149082178
- Cited by
- 677
- References
- 7
- Type
- posted content
- Language
- en
- Open access
- bronze
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