Cite as: Cold Spring Harb. Protoc.; 2008; doi:10.1101/pdb.top46

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topic_introductionTopic Introduction

Copy Number Variation Detection via High-Density SNP Genotyping

Kai Wang1 and Maja Bucan

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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Related Article

PennCNV: An integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data
Kai Wang, Mingyao Li, Dexter Hadley, Rui Liu, Joseph Glessner, Struan F.A. Grant, Hakon Hakonarson, and Maja Bucan
Genome Res. 17: 1665-1674. [Abstract] [Full Text]