Tree inference for single-cell data

Genome Biology

Volumn 17, Issue 1, 2016, Pages

  Jahn, Katharina ^a,b   Kuipers, Jack ^a,b   Beerenwinkel, Niko ^a,b  

^a ETH ZURICH   (Switzerland)

^b SWISS INSTITUTE OF BIOINFORMATICS   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

JANUS KINASE 2; DNA;

ALGORITHM; ARTICLE; DATA PROCESSING; ESTROGEN RECEPTOR POSITIVE BREAST CANCER; GENETIC VARIATION; HETEROZYGOSITY; HOMOZYGOSITY; HUMAN; KIDNEY CARCINOMA; MARKOV CHAIN; MAXIMUM LIKELIHOOD METHOD; MONTE CARLO METHOD; MUTATION; MYELOPROLIFERATIVE NEOPLASM; PROBABILITY; SEQUENCE ANALYSIS; SIMULATION; SINGLE CELL INFERENCE OF TUMOR EVOLUTION; SINGLE NUCLEOTIDE VARIATION; TUMOR GROWTH; CHEMISTRY; CLONAL EVOLUTION; DNA SEQUENCE; GENETIC HETEROGENEITY; GENETICS; NEOPLASM; PROCEDURES; SENSITIVITY AND SPECIFICITY; SINGLE CELL ANALYSIS; SOFTWARE; STANDARDS;

CLONAL EVOLUTION; DNA, NEOPLASM; GENETIC HETEROGENEITY; HUMANS; MUTATION; NEOPLASMS; SENSITIVITY AND SPECIFICITY; SEQUENCE ANALYSIS, DNA; SINGLE-CELL ANALYSIS; SOFTWARE;

EID: 84965070761     PISSN: 14747596     EISSN: 1474760X     Source Type: Journal    
DOI: 10.1186/s13059-016-0936-x     Document Type: Article

References (41)

1. Nowell PC. The clonal evolution of tumor cell populations. Science. 1976; 194:23-8.
2. Merlo LM, Pepper JW, Reid BJ, Maley CC. Cancer as an evolutionary and ecological process. Nat Rev Cancer. 2006; 6:924-35.
3. Pepper JW, Scott Findlay C, Kassen R, Spencer SL, Maley CC. Synthesis: cancer research meets evolutionary biology. Evol Appl. 2009; 2:62-70.
4. Nik-Zainal S, Van Loo P, Wedge DC, Alexandrov LB, Greenman CD, Lau KW, Raine K, Jones D, Marshall J, Ramakrishna M, et al. The life history of 21 breast cancers. Cell. 2012; 149:994-1007.
5. Yates LR, Campbell PJ. Evolution of the cancer genome. Nat Rev Genet. 2012; 13:795-806.
6. Greaves M, Maley CC. Clonal evolution in cancer. Nature. 2012; 481:306-13.
7. Ding L, Ley TJ, Larson DE, Miller CA, Koboldt DC, Welch JS, Ritchey JK, Young MA, Lamprecht T, McLellan MD, et al. Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing. Nature. 2012; 481:506-10.
8. Gillies RJ, Verduzco D, Gatenby RA. Evolutionary dynamics of carcinogenesis and why targeted therapy does not work. Nat Rev Cancer. 2012; 12:487-93.
9. Ortmann CA, Kent DG, Nangalia J, Silber Y, Wedge DC, Grinfeld J, Baxter EJ, Massie CE, Papaemmanuil E, Menon S, et al. Effect of mutation order on myeloproliferative neoplasms. N Engl J Med. 2015; 372:601-12.
10. Stratton MR, Campbell PJ, Futreal PA. The cancer genome. Nature. 2009; 458:719-24.
11. Swanton C. Intratumor heterogeneity: evolution through space and time. Cancer Res. 2012; 72:4875-82.
12. Gusfield D. Algorithms on strings, trees and sequences: computer science and computational biology. Cambridge: Cambridge University Press; 1997.
13. Navin NE. Cancer genomics: one cell at a time. Genome Biol. 2014; 15:452.
14. Gerstung M, Beisel C, Rechsteiner M, Wild P, Schraml P, Moch H, Beerenwinkel N. Reliable detection of subclonal single-nucleotide variants in tumour cell populations. Nat Commun. 2012; 3:811.
15. Shah SP, Roth A, Goya R, Oloumi A, Ha G, Zhao Y, Turashvili G, Ding J, Tse K, Haffari G, et al. The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature. 2012; 486:395-9.
16. Roth A, Khattra J, Yap D, Wan A, Laks E, Biele J, Ha G, Aparicio S, Bouchard-Côté A, Shah SP. Pyclone: statistical inference of clonal population structure in cancer. Nat Methods. 2014; 11:396-8.
17. Ha G, Roth A, Khattra J, Ho J, Yap D, Prentice LM, Melnyk N, McPherson A, Bashashati A, Laks E, et al. Titan: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data. Genome Res. 2014; 24:1881-93.
18. Oesper L, Mahmoody A, Raphael BJ. Theta: inferring intra-tumor heterogeneity from high-throughput dna sequencing data. Genome Biol. 2013; 14:80.
19. Zare H, Wang J, Hu A, Weber K, Smith J, Nickerson D, Song C, Witten D, Blau CA, Noble WS. Inferring clonal composition from multiple sections of a breast cancer. PLoS Comput Biol. 2014; 10:003703.
20. Strino F, Parisi F, Micsinai M, Kluger Y. Trap: a tree approach for fingerprinting subclonal tumor composition. Nucleic Acids Res. 2013; 41:165-5.
21. Hajirasouliha I, Mahmoody A, Raphael BJ. A combinatorial approach for analyzing intra-tumor heterogeneity from high-throughput sequencing data. Bioinformatics. 2014; 30:78-86.
22. El-Kebir M, Oesper L, Acheson-Field H, Raphael BJ. Reconstruction of clonal trees and tumor composition from multi-sample sequencing data. Bioinformatics. 2015; 31:62-70.
23. Qiao Y, Quinlan AR, Jazaeri AA, Verhaak RG, Wheeler DA, Marth GT. Subcloneseeker: a computational framework for reconstructing tumor clone structure for cancer variant interpretation and prioritization. Genome Biol. 2014; 15:443.
24. Deshwar AG, Vembu S, Yung CK, Jang GH, Stein L, Morris Q. PhyloWGS: Reconstructing subclonal composition and evolution from whole-genome sequencing of tumors. Genome Biol. 2015; 16:35.
25. Jiao W, Vembu S, Deshwar AG, Stein L, Morris Q. Inferring clonal evolution of tumors from single nucleotide somatic mutations. BMC Bioinform. 2014; 15:35.
26. Malikic S, McPherson AW, Donmez N, Sahinalp CS. Clonality inference in multiple tumor samples using phylogeny. Bioinformatics. 2015; 31:1349-56.
27. Popic V, Salari R, Hajirasouliha I, Kashef-Haghighi D, West RB, Batzoglou S. Fast and scalable inference of multi-sample cancer lineages. Genome Biol. 2015; 16:91.
28. Schuh A, Becq J, Humphray S, Alexa A, Burns A, Clifford R, Feller SM, Grocock R, Henderson S, Khrebtukova I, et al. Monitoring chronic lymphocytic leukemia progression by whole genome sequencing reveals heterogeneous clonal evolution patterns. Blood. 2012; 120:4191-6.
29. Van Loo P, Voet T. Single cell analysis of cancer genomes. Curr Opinion Genet Dev. 2014; 24:82-91.
30. Hou Y, Song L, Zhu P, Zhang B, Tao Y, Xu X, Li F, Wu K, Liang J, Shao D, et al. Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm. Cell. 2012; 148:873-85.
31. Chen D, Eulenstein O, Fernandez-Baca D, Sanderson M. Minimum-flip supertrees: complexity and algorithms. IEEE/ACM Trans Comput Biol Bioinform. 2006; 3:165-73.
32. Gusfield D, Frid Y, Brown D. Integer programming formulations and computations solving phylogenetic and population genetic problems with missing or genotypic data. In: Computing and combinatorics. Berlin: Springer: 2007. p. 51-64.
33. Yuan K, Sakoparnig T, Markowetz F, Beerenwinkel N. BitPhylogeny: a probabilistic framework for reconstructing intra-tumor phylogenies. Genome Biol. 2015; 16:36.
34. Kim KI, Simon R. Using single cell sequencing data to model the evolutionary history of a tumor. BMC Bioinform. 2014; 15:27.
35. Xu X, Hou Y, Yin X, Bao L, Tang A, Song L, Li F, Tsang S, Wu K, Wu H, et al. Single-cell exome sequencing reveals single-nucleotide mutation characteristics of a kidney tumor. Cell. 2012; 148:886-95.
36. Wang Y, Waters J, Leung ML, Unruh A, Roh W, Shi X, Chen K, Scheet P, Vattathil S, Liang H, et al. Clonal evolution in breast cancer revealed by single nucleus genome sequencing. Nature. 2014; 512:155-60.
37. Kuipers J, Moffa G. Uniform random generation of large acyclic digraphs. Stat Comput. 2015; 25:227-42.
38. Friedman N, Koller D. Being Bayesian about network structure. A Bayesian approach to structure discovery in Bayesian networks. Mach Learn. 2003; 50:95-125.
39. Kuipers J, Moffa G. Partition MCMC for inference on acyclic digraphs. J Am Stat Assoc. 2016. doi: http://dx.doi.org/10.1080/01621459.2015.1133426.
40. Markowetz F, Kostka D, Troyanskaya OG, Spang R. Nested effects models for high-dimensional phenotyping screens. Bioinformatics. 2007; 23:305-12.
41. Madigan D, York J. Bayesian graphical models for discrete data. Int Stat Rev. 1995; 63:215-32.