COKGEN: Identification of Copy Number Variants Using Optimization
COKGEN is an R Package for identification of copy number variants using SNP microarray data.
Unlike existing model-based methods that train their models based on common variations, COKGEN
uses an explicitly designed objective function that aims to trade-off noise and parsimony
using only a few adjustable parameters. These parameters can be configured
based on the characteristics of the experimental platform and target application, so that the
solution to the optimization problem is the most accurate set of CNV calls.
These characteristics make COKGEN particularly useful for identification of rare copy number
variants.
COKGEN was developed by Gokhan Yavas, Mehmet Koyuturk,
and Tom LaFramboise at
Case Western Reserve University.
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Publications
- G. Yavas, M. Koyuturk, and T. LaFramboise.
Optimization algorithms for identification and genotyping of copy number polymorphisms
in human populations. 5th IAPR Int'l Conf. on Pattern
Recognition in Bioinformatics (PRIB'10), 74-85, 2010.
- G. Yavas, M. Koyuturk, M. Ozsoyoglu, M. P. Gould, and T. LaFramboise.
COKGEN:
A software for the identification of rare copy number variation from SNP microarrays.
Pacific
Symposium on Biocomputing (PSB'10), 371-382, 2010.
- G. Yavas, M. Koyuturk, M. Ozsoyoglu, M. P. Gould, and T. LaFramboise.
An optimization
framework for unsupervised identification of rare copy number variation from SNP array
data.
Genome Biology, 10:R119, 2009.
Acknowledgments
Development of COKGEN is supported
by National Science Foundation
Award IIS-0916102.