PMID- 23527109
OWN - NLM
STAT- MEDLINE
DCOM- 20130927
LR  - 20211021
IS  - 1932-6203 (Electronic)
IS  - 1932-6203 (Linking)
VI  - 8
IP  - 3
DP  - 2013
TI  - Comparative studies of copy number variation detection methods for 
      next-generation sequencing technologies.
PG  - e59128
LID - 10.1371/journal.pone.0059128 [doi]
LID - e59128
AB  - Copy number variation (CNV) has played an important role in studies of 
      susceptibility or resistance to complex diseases. Traditional methods such as 
      fluorescence in situ hybridization (FISH) and array comparative genomic 
      hybridization (aCGH) suffer from low resolution of genomic regions. Following the 
      emergence of next generation sequencing (NGS) technologies, CNV detection methods 
      based on the short read data have recently been developed. However, due to the 
      relatively young age of the procedures, their performance is not fully 
      understood. To help investigators choose suitable methods to detect CNVs, 
      comparative studies are needed. We compared six publicly available CNV detection 
      methods: CNV-seq, FREEC, readDepth, CNVnator, SegSeq and event-wise testing 
      (EWT). They are evaluated both on simulated and real data with different 
      experiment settings. The receiver operating characteristic (ROC) curve is 
      employed to demonstrate the detection performance in terms of sensitivity and 
      specificity, box plot is employed to compare their performances in terms of 
      breakpoint and copy number estimation, Venn diagram is employed to show the 
      consistency among these methods, and F-score is employed to show the overlapping 
      quality of detected CNVs. The computational demands are also studied. The results 
      of our work provide a comprehensive evaluation on the performances of the 
      selected CNV detection methods, which will help biological investigators choose 
      the best possible method.
FAU - Duan, Junbo
AU  - Duan J
AD  - Department of Biomedical Engineering, Tulane University, New Orleans, Louisiana, 
      United States of America.
FAU - Zhang, Ji-Gang
AU  - Zhang JG
FAU - Deng, Hong-Wen
AU  - Deng HW
FAU - Wang, Yu-Ping
AU  - Wang YP
LA  - eng
GR  - R01 AR050496/AR/NIAMS NIH HHS/United States
GR  - R01 AR057049/AR/NIAMS NIH HHS/United States
GR  - R01 AR059781/AR/NIAMS NIH HHS/United States
PT  - Comparative Study
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, U.S. Gov't, Non-P.H.S.
DEP - 20130320
PL  - United States
TA  - PLoS One
JT  - PloS one
JID - 101285081
SB  - IM
MH  - Computer Simulation
MH  - *DNA Copy Number Variations
MH  - Genomics/methods
MH  - High-Throughput Nucleotide Sequencing/*methods
MH  - Humans
MH  - ROC Curve
MH  - Reproducibility of Results
PMC - PMC3604020
COIS- Competing Interests: The authors have declared that no competing interests exist.
EDAT- 2013/03/26 06:00
MHDA- 2013/09/28 06:00
PMCR- 2013/03/20
CRDT- 2013/03/26 06:00
PHST- 2012/06/20 00:00 [received]
PHST- 2013/02/12 00:00 [accepted]
PHST- 2013/03/26 06:00 [entrez]
PHST- 2013/03/26 06:00 [pubmed]
PHST- 2013/09/28 06:00 [medline]
PHST- 2013/03/20 00:00 [pmc-release]
AID - PONE-D-12-18295 [pii]
AID - 10.1371/journal.pone.0059128 [doi]
PST - ppublish
SO  - PLoS One. 2013;8(3):e59128. doi: 10.1371/journal.pone.0059128. Epub 2013 Mar 20.