PMID- 27688796
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20160930
LR  - 20240326
IS  - 1748-7188 (Print)
IS  - 1748-7188 (Electronic)
IS  - 1748-7188 (Linking)
VI  - 11
DP  - 2016
TI  - Analysis of gene copy number changes in tumor phylogenetics.
PG  - 26
LID - 10.1186/s13015-016-0088-2 [doi]
LID - 26
AB  - BACKGOUND: Evolution of cancer cells is characterized by large scale and rapid 
      changes in the chromosomal  landscape. The fluorescence in situ hybridization 
      (FISH) technique provides a way to measure the copy numbers of preselected genes 
      in a group of cells and has been found to be a reliable source of data to model 
      the evolution of tumor cells. Chowdhury et al. (Bioinformatics 29(13):189-98, 23; 
      PLoS Comput Biol 10(7):1003740, 24) recently develop a computational model for 
      tumor progression driven by gains and losses in cell count patterns obtained by 
      FISH probes. Their model aims to find the rectilinear Steiner minimum tree (RSMT) 
      (Chowdhury et al. in Bioinformatics 29(13):189-98, 23) and the duplication 
      Steiner minimum tree (DSMT) (Chowdhury et al. in PLoS Comput Biol 10(7):1003740, 
      24) that describe the progression of FISH cell count patterns over its branches 
      in a parsimonious manner. Both the RSMT and DSMT problems are NP-hard and 
      heuristics are required to solve the problems efficiently. METHODS: In this paper 
      we propose two approaches to solve the RSMT problem, one inspired by iterative 
      methods to address the "small phylogeny" problem (Sankoff et al. in J Mol Evol 
      7(2):133-49, 27; Blanchette et al. in Genome Inform 8:25-34, 28), and the other 
      based on maximum parsimony phylogeny inference. We further show how to extend 
      these heuristics to obtain solutions to the DSMT problem, that models large scale 
      duplication events. RESULTS: Experimental results from both simulated and real 
      tumor data show that our methods outperform previous heuristics (Chowdhury et al. 
      in Bioinformatics 29(13):189-98, 23; Chowdhury et al. in PLoS Comput Biol 
      10(7):1003740, 24) in obtaining solutions to both RSMT and DSMT problems. 
      CONCLUSION: The methods introduced here are able to provide more parsimony 
      phylogenies compared to earlier ones which are consider better choices.
FAU - Zhou, Jun
AU  - Zhou J
AD  - School of Computer Science and Technology, Tianjin University, Tianjin, 300072 
      China ; Department of Computer Science and Engineering, University of South 
      Carolina, Columbia, SC 29208 USA.
FAU - Lin, Yu
AU  - Lin Y
AD  - Research School of Computer Science, Australian National University, Canberra, 
      ACT 0200 Australia.
FAU - Rajan, Vaibhav
AU  - Rajan V
AD  - Xerox Research Centre India (XRCI), Bangalore, India.
FAU - Hoskins, William
AU  - Hoskins W
AD  - Department of Computer Science and Engineering, University of South Carolina, 
      Columbia, SC 29208 USA.
FAU - Feng, Bing
AU  - Feng B
AD  - Department of Computer Science and Engineering, University of South Carolina, 
      Columbia, SC 29208 USA.
FAU - Tang, Jijun
AU  - Tang J
AD  - Department of Computer Science and Engineering, University of South Carolina, 
      Columbia, SC 29208 USA.
LA  - eng
PT  - Journal Article
DEP - 20160922
PL  - England
TA  - Algorithms Mol Biol
JT  - Algorithms for molecular biology : AMB
JID - 101265088
PMC - PMC5034472
OTO - NOTNLM
OT  - Chromosomal duplication
OT  - FISH
OT  - Gene copy number
OT  - Gene duplication
OT  - Maximum parsimony
OT  - Rectilinear Steiner minimum tree
OT  - Tumor phylogeny
OT  - Whole genome duplication
EDAT- 2016/10/01 06:00
MHDA- 2016/10/01 06:01
PMCR- 2016/09/22
CRDT- 2016/10/01 06:00
PHST- 2016/01/22 00:00 [received]
PHST- 2016/09/08 00:00 [accepted]
PHST- 2016/10/01 06:00 [entrez]
PHST- 2016/10/01 06:00 [pubmed]
PHST- 2016/10/01 06:01 [medline]
PHST- 2016/09/22 00:00 [pmc-release]
AID - 88 [pii]
AID - 10.1186/s13015-016-0088-2 [doi]
PST - epublish
SO  - Algorithms Mol Biol. 2016 Sep 22;11:26. doi: 10.1186/s13015-016-0088-2. 
      eCollection 2016.