HapMuC: Somatic mutation calling using heterozygous germ line variants near candidate mutations

Bioinformatics

Volumn 30, Issue 23, 2014, Pages 3302-3309

  Usuyama, Naoto ^a   Shiraishi, Yuichi ^a   Sato, Yusuke ^b,c   Kume, Haruki ^b   Homma, Yukio ^b   Ogawa, Seishi ^c   Miyano, Satoru ^a   Imoto, Seiya ^a  

^a UNIVERSITY OF TOKYO   (Japan)

^b UNIVERSITY OF TOKYO   (Japan)

^c KYOTO UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; BAYES THEOREM; GENE FREQUENCY; GENETICS; HAPLOTYPE; HETEROZYGOTE; HUMAN; MUTATION; NEOPLASM; NUCLEOTIDE SEQUENCE; PROCEDURES; SINGLE NUCLEOTIDE POLYMORPHISM; TUMOR CELL LINE;

ALGORITHMS; BAYES THEOREM; CELL LINE, TUMOR; DNA MUTATIONAL ANALYSIS; GENE FREQUENCY; HAPLOTYPES; HETEROZYGOTE; HUMANS; MUTATION; NEOPLASMS; POLYMORPHISM, SINGLE NUCLEOTIDE;

EID: 84925550822     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btu537     Document Type: Article

References (34)

1. Albers, C.A. et al. (2011) Dindel: accurate indel calls from short-read data. Genome Res., 21, 961-973.
2. Beal, M.J. (2003) Variational Algorithms for Approximate Bayesian Inference. PhD thesis, The Gatsby Computational Neuroscience Unit, University College London, London, UK.
3. Benson, G. (1999) Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res., 27, 573.
4. Blei, D.M. et al. (2003) Latent dirichlet allocation. J. Mach. Learn. Res., 3, 993-1022.
5. Bradley, A.P. (1997) The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognit., 30, 1145-1159.
6. Chiaromonte, F. et al. (2002) Scoring pairwise genomic sequence alignments. In: Pacific Symposium on Biocomputing. Vol. 7, pp. 115-126.
7. Cibulskis, K. et al. (2013) Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat. Biotechnol., 31, 213-219.
8. Cilibrasi, R. et al. (2005) On the complexity of several haplotyping problems. In: Algorithms in Bioinformatics. Springer, pp. 128-139.
9. Ding, L. et al. (2012) Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing. Nature, 481, 506-510.
10. Eddy, S.R. (1998) Profile hidden Markov models. Bioinformatics, 14, 755-763.
11. Fawcett, T. (2006) An introduction to ROC analysis. Pattern Recognit. Lett., 27, 861-874.
12. 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.
13. Genovese, G. et al. (2013) Mapping the human reference genomes missing sequence by three-way admixture in latino genomes. Am. J. Hum. Genet., 93, 411-421.
14. Genovese, L.M. et al. (2008) Speedhap: an accurate heuristic for the single individual SNP haplotyping problem with many gaps, high reading error rate and low coverage. IEEE/ACM Trans. Comput. Biol. Bioinform., 5, 492-502.
15. Goya, R. et al. (2010) SNVMix: predicting single nucleotide variants from next-generation sequencing of tumors. Bioinformatics, 26, 730-736.
16. He, D. et al. (2010) Optimal algorithms for haplotype assembly from whole-genome sequence data. Bioinformatics, 26, i183-i190.
17. Kent, W.J. (2002) BLAT-the BLAST-like alignment tool. Genome Res., 12, 656-664.
18. Kent, W.J. et al. (2003) Evolution's cauldron: duplication, deletion, and rearrangement in the mouse and human genomes. Proc. Natl Acad. Sci. USA, 100, 11484-11489.
19. Koboldt, D.C. et al. (2012) VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res., 22, 568-576.
20. Larson, D.E. et al. (2012) SomaticSniper: identification of somatic point mutations in whole genome sequencing data. Bioinformatics, 28, 311-317.
21. Ley, T.J. et al. (2008) DNA sequencing of a cytogenetically normal acute myeloid leukaemia genome. Nature, 456, 66-72.
22. Meyerson, M. et al. (2010) Advances in understanding cancer genomes through second-generation sequencing. Nat. Rev. Genet., 11, 685-696.
23. Nik-Zainal, S. et al. (2012) The life history of 21 breast cancers. Cell, 149, 994-1007.
24. Pleasance, E.D. et al. (2010) A comprehensive catalogue of somatic mutations from a human cancer genome. Nature, 463, 191-196.
25. Robin, X. et al. (2011) pROC: an open-source package for R and S+to analyze and compare ROC curves. BMC Bioinformatics, 12, 77.
26. Roth, A. et al. (2012) JointSNVMix: a probabilistic model for accurate detection of somatic mutations in normal/tumour paired next-generation sequencing data. Bioinformatics, 28, 907-913.
27. Sato, Y. et al. (2013) Integrated molecular analysis of clear-cell renal cell carcinoma. Nat. Genet., 45, 860-867.
28. Saunders, C.T. et al. (2012) Strelka: accurate somatic small-variant calling from sequenced tumor-normal sample pairs. Bioinformatics, 28, 1811-1817.
29. Schwartz, S. et al. (2003) Human-mouse alignments with BLASTZ. Genome Res., 13, 103-107.
30. Shah, S.P. et al. (2009) Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution. Nature, 461, 809-813.
31. Sherry, S.T. et al. (2001) dbSNP: the NCBI database of genetic variation. Nucleic Acids Res., 29, 308-311.
32. Shiraishi, Y. et al. (2013) An empirical Bayesian framework for somatic mutation detection from cancer genome sequencing data. Nucleic Acids Res., 41, e89-e89.
33. Thorvaldsdóttir, H. et al. (2013) Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief. Bioinform., 14, 178-192.
34. Yoshida, K. et al. (2011) Frequent pathway mutations of splicing machinery in myelodysplasia. Nature, 478, 64-69.