Subclonal variant calling with multiple samples and prior knowledge

Bioinformatics

Volumn 30, Issue 9, 2014, Pages 1198-1204

  Gerstung, Moritz ^a   Papaemmanuil, Elli ^a   Campbell, Peter J ^a,b,c  

^a WELLCOME TRUST SANGER INSTITUTE   (United Kingdom)

^b ADDENBROOKE S HOSPITAL   (United Kingdom)

^c UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; BIOMETRY; COMPUTER PROGRAM; GENETICS; HUMAN; HUMAN GENOME; MUTATION; NEOPLASM; PROBABILITY; PROGNOSIS; REPRODUCIBILITY;

ALGORITHMS; BIOMETRY; GENOME, HUMAN; HUMANS; MUTATION; NEOPLASMS; PROBABILITY; PROGNOSIS; REPRODUCIBILITY OF RESULTS; SOFTWARE DESIGN;

EID: 84899477038     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btt750     Document Type: Article

References (19)

1. Cibulskis, K. et al. (2013) Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat. Biotechnol., 31, 213-219.
2. Damm, F. et al. (2012) Mutations affecting mRNA splicing define distinct clinical phenotypes and correlate with patient outcome in myelodysplastic syndromes. Blood, 119, 3211-3218.
3. Forbes, S.A. et al. (2011) COSMIC: mining complete cancer genomes in the catalogue of somatic mutations in cancer. Nucleic Acids Res., 39, D945-D950.
4. Gerstung, M. et al. (2012) Reliable detection of subclonal single-nucleotide variants in tumour cell populations. Nat. Commun., 3, 811.
5. Goya, R. et al. (2010) SNVMix: predicting single nucleotide variants from next generation sequencing of tumors. Bioinformatics, 26, 730-736.
6. Harrell, F.E. Jr et al. (1996) Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat. Med., 15, 361-387.
7. Kim, S.Y. and Speed, T.P. (2013) Comparing somatic mutation-callers: beyond Venn diagrams. BMC Bioinformatics, 14, 189.
8. Landau, D.A. et al. (2013) Evolution and impact of subclonal mutations in chronic lymphocytic leukemia. Cell, 152, 714-726.
9. Larson, D.E. et al. (2011) SomaticSniper: identification of somatic point mutations in whole genome sequencing data. Bioinformatics, 28, 311-317.
10. Li, H. and Durbin, R. (2010) Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics, 26, 589-595.
11. Malcovati, L. et al. (2011) Clinical significance of SF3B1 mutations in myelodysplastic syndromes and myelodysplastic/myeloproliferative neoplasms. Blood, 118, 6239-6246.
12. Nik-Zainal, S. et al. (2012) The life history of 21 breast cancers. Cell, 149, 994-1007.
13. Papaemmanuil, E. et al. (2011) Somatic SF3B1 mutation in myelodysplasia with ring sideroblasts. N. Engl. J. Med., 365, 1384-1395.
14. Papaemmanuil, E. et al. (2013) Clinical and biological implications of driver mutations in myelodysplastic syndromes. Blood, 122, 3616-3627.
15. R Core Team. (2012) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, ISBN 3-900051-07-0.
16. Schmitt, M.W. et al. (2012) Detection of ultra-rare mutations by next-generation sequencing. Proc. Natl Acad. Sci. USA, 109, 14508-14513.
17. Stephens, P.J. et al. (2012) The landscape of cancer genes and mutational processes in breast cancer. Nature, 486, 400-404.
18. Stratton, M.R. (2011) Exploring the genomes of cancer cells: progress and promise. Science, 331, 1553-1558.
19. Yates, L.R. and Campbell, P.J. (2012) Evolution of the cancer genome. Nat. Rev. Genet., 13, 795-806.