Genome-wide mapping of copy number variation in humans: comparative analysis of high resolution array platforms

Accurate and efficient genome-wide detection of copy number variants (CNVs) is essential for understanding human genomic variation, genome-wide CNV association type studies, cytogenetics research and diagnostics, and independent validation of CNVs identified from sequencing based technologies. Numer...

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Bibliographic Details
Published in:PloS one 2011-11, Vol.6 (11), p.e27859-e27859
Main Authors: Haraksingh, Rajini R, Abyzov, Alexej, Gerstein, Mark, Urban, Alexander E, Snyder, Michael
Format: Article
Language:English
Subjects:
Algorithms
Arrays
Base Pairing - genetics
Biochemistry
Biology
Biophysics
Chromosome Mapping - methods
Chromosomes, Human, Pair 1 - genetics
Comparative analysis
Congenital diseases
Consortia
Copy number
Cytogenetics
Deoxyribonucleic acid
Developmental disabilities
Diagnostic tests
DNA
DNA Copy Number Variations - genetics
Gene mapping
Gene sequencing
Genes
Genome, Human - genetics
Genomes
Genomics
Genotyping
High resolution
Humans
Hybridization
Intellectual disabilities
Medicine
Oligonucleotide Array Sequence Analysis - methods
Platforms
Polymorphism
Reference Standards
Single nucleotide polymorphisms
Single-nucleotide polymorphism
Studies
Therapeutic applications
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Summary:Accurate and efficient genome-wide detection of copy number variants (CNVs) is essential for understanding human genomic variation, genome-wide CNV association type studies, cytogenetics research and diagnostics, and independent validation of CNVs identified from sequencing based technologies. Numerous, array-based platforms for CNV detection exist utilizing array Comparative Genome Hybridization (aCGH), Single Nucleotide Polymorphism (SNP) genotyping or both. We have quantitatively assessed the abilities of twelve leading genome-wide CNV detection platforms to accurately detect Gold Standard sets of CNVs in the genome of HapMap CEU sample NA12878, and found significant differences in performance. The technologies analyzed were the NimbleGen 4.2 M, 2.1 M and 3×720 K Whole Genome and CNV focused arrays, the Agilent 1×1 M CGH and High Resolution and 2×400 K CNV and SNP+CGH arrays, the Illumina Human Omni1Quad array and the Affymetrix SNP 6.0 array. The Gold Standards used were a 1000 Genomes Project sequencing-based set of 3997 validated CNVs and an ultra high-resolution aCGH-based set of 756 validated CNVs. We found that sensitivity, total number, size range and breakpoint resolution of CNV calls were highest for CNV focused arrays. Our results are important for cost effective CNV detection and validation for both basic and clinical applications.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0027859