PMID- 21328710
OWN - NLM
STAT- MEDLINE
DCOM- 20110614
LR  - 20211020
IS  - 1757-6334 (Electronic)
IS  - 0219-7200 (Print)
IS  - 0219-7200 (Linking)
VI  - 9
IP  - 1
DP  - 2011 Feb
TI  - A novel approach to DNA copy number data segmentation.
PG  - 131-48
AB  - DNA copy number (DCN) is the number of copies of DNA at a region of a genome. The 
      alterations of DCN are highly associated with the development of different 
      tumors. Recently, microarray technologies are being employed to detect DCN 
      changes at many loci at the same time in tumor samples. The resulting DCN data 
      are often very noisy, and the tumor sample is often contaminated by normal cells. 
      The goal of computational analysis of array-based DCN data is to infer the 
      underlying DCNs from raw DCN data. Previous methods for this task do not model 
      the tumor/normal cell mixture ratio explicitly and they cannot output segments 
      with DCN annotations. We developed a novel model-based method using the minimum 
      description length (MDL) principle for DCN data segmentation. Our new method can 
      output underlying DCN for each chromosomal segment, and at the same time, infer 
      the underlying tumor proportion in the test samples. Empirical results show that 
      our method achieves better accuracies on average as compared to three previous 
      methods, namely Circular Binary Segmentation, Hidden Markov Model and Ultrasome.
FAU - Wang, Siling
AU  - Wang S
AD  - Department of Computer Science and Engineering, Southern Methodist University, 
      Dallas, Texas 75205, USA. silingw@smu.edu
FAU - Wang, Yuhang
AU  - Wang Y
FAU - Xie, Yang
AU  - Xie Y
FAU - Xiao, Guanghua
AU  - Xiao G
LA  - eng
GR  - R33 DA027592/DA/NIDA NIH HHS/United States
GR  - 1R01CA152301-01/CA/NCI NIH HHS/United States
GR  - R21 DA027592-02/DA/NIDA NIH HHS/United States
GR  - 1R21DA027592/DA/NIDA NIH HHS/United States
GR  - R01 CA152301/CA/NCI NIH HHS/United States
GR  - R21 DA027592/DA/NIDA NIH HHS/United States
PT  - Comparative Study
PT  - Evaluation Study
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, U.S. Gov't, Non-P.H.S.
PL  - Singapore
TA  - J Bioinform Comput Biol
JT  - Journal of bioinformatics and computational biology
JID - 101187344
RN  - 0 (DNA, Neoplasm)
SB  - IM
MH  - Algorithms
MH  - Computational Biology
MH  - Computer Simulation
MH  - *DNA Copy Number Variations
MH  - DNA, Neoplasm/genetics
MH  - Data Interpretation, Statistical
MH  - Databases, Nucleic Acid/statistics & numerical data
MH  - Humans
MH  - Markov Chains
MH  - Models, Statistical
MH  - Neoplasms/genetics
MH  - Oligonucleotide Array Sequence Analysis/statistics & numerical data
MH  - Software
PMC - PMC3084615
MID - NIHMS288631
EDAT- 2011/02/18 06:00
MHDA- 2011/06/15 06:00
PMCR- 2011/04/29
CRDT- 2011/02/18 06:00
PHST- 2010/02/10 00:00 [received]
PHST- 2010/11/02 00:00 [revised]
PHST- 2010/11/04 00:00 [accepted]
PHST- 2011/02/18 06:00 [entrez]
PHST- 2011/02/18 06:00 [pubmed]
PHST- 2011/06/15 06:00 [medline]
PHST- 2011/04/29 00:00 [pmc-release]
AID - S0219720011005343 [pii]
AID - 10.1142/s0219720011005343 [doi]
PST - ppublish
SO  - J Bioinform Comput Biol. 2011 Feb;9(1):131-48. doi: 10.1142/s0219720011005343.