Cite as: Cold Spring Harb. Protoc.; 2008; doi:10.1101/pdb.top46
| Topic Introduction |
Department of Genetics, University of Pennsylvania, Philadelphia, PA 19446, USA
1Corresponding author (kai{at}mail.med.upenn.edu)
INTRODUCTION
High-density single nucleotide polymorphism (SNP) genotyping arrays recently have been used for copy number variation (CNV) detection and analysis, because the arrays can serve a dual role for SNP- and CNV-based association studies. They also can provide considerably higher precision and resolution than traditional techniques. Here we describe PennCNV, a computational protocol designed for CNV detection from high-density SNP genotyping data. This protocol extracts allele-specific signal intensities from genotyping arrays, and then integrates information on SNP spacing and SNP allele frequencies to generate CNV calls by a hidden Markov model (HMM) algorithm. Analyses of CNVs from SNP genotyping arrays will provide a more comprehensive view of genome variation, and complement current genome-wide association studies in identifying disease susceptibility loci.
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