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PMID: 19267900 Published · epublish English Journal Article Research Support, Non-U.S. Gov't

CNV-seq, a new method to detect copy number variation using high-throughput sequencing.

BMC bioinformatics ·Vol. 10 ·2009-03-06 ·Pages 80

Xie C, Tammi MT

Abstract

DNA copy number variation (CNV) has been recognized as an important source of genetic variation. Array comparative genomic hybridization (aCGH) is commonly used for CNV detection, but the microarray platform has a number of inherent limitations. Here, we describe a method to detect copy number variation using shotgun sequencing, CNV-seq. The method is based on a robust statistical model that describes the complete analysis procedure and allows the computation of essential confidence values for detection of CNV. Our results show that the number of reads, not the length of the reads is the key factor determining the resolution of detection. This favors the next-generation sequencing methods that rapidly produce large amount of short reads. Simulation of various sequencing methods with coverage between 0.1x to 8x show overall specificity between 91.7 - 99.9%, and sensitivity between 72.2 - 96.5%. We also show the results for assessment of CNV between two individual human genomes.

MeSH Terms
Algorithms DNA/chemistry Gene Dosage Genetic Variation/genetics Genome, Human Genomics/methods Humans Sequence Analysis, DNA/methods
Chemicals
DNA
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Xie Chao
Department of Biological Sciences, National University of Singapore, Singapore. [email protected]
Tammi Martti T
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Article Info
Journal
BMC bioinformatics
Abbr.
BMC Bioinformatics
ISSN
1471-2105
Published
2009-03-06
Epub
2009-00-06
Pages
80
Language
English
Region
England
NLM ID
100965194
PMCID
PMC2667514
Subset
IM
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