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Download the Paper (3.0 MB, PDF file) - January 1, 2008 Tell a colleague about it. Printing Tips: Select 'print as image' in the Acrobat print dialog if you have trouble printing.

ABSTRACT:
We develop an algorithm to analyze data from Illumina genotyping arrays for the detection of copy number variations in a single individual or in a random sample of individuals. We use a Hidden Markov Model framework, appropriately extended to take into account linkage disequilibrium between nearby loci. We describe a multisample approach to estimate the frequency of copy number variants in the population. With appropriate dataset, our methodology simultaneously analyzes the data for copy-number variation and tests for association between this and a disease trait of interest.

SUGGESTED CITATION:
Hui Wang, Jan Veldink, Roel Opoff, and Chiara Sabatti, "Markov models for inferring Copy Number Variations from genotype data" (January 1, 2008). Department of Statistics, UCLA. Department of Statistics Papers. Paper 2008010102.
http://repositories.cdlib.org/uclastat/papers/2008010102