Ontology highlight
ABSTRACT: We present a database of copy number variations (CNVs) detected in 2,026 disease-free individuals, using high-density, SNP-based
oligonucleotide microarrays. This large cohort analyzed for CNVs in a single study using a uniform array platform and
computational tools, comprises mainly of Caucasians (65.2%) and African-Americans (34.2%), We have catalogued and
characterized 54,462 individual CNVs, 77.8% of which were identified in multiple unrelated individuals. These non-unique CNVs
mapped to 3,272 distinct regions of genomic variation spanning 5.9% of the genome; 51.5% of these were previously unreported,
and >85% are rare. Our annotation and analysis confirmed and extended previously reported correlations between CNVs and several
genomic features such as repetitive DNA elements, segmental duplications and genes. We demonstrate the utility of this data set
in distinguishing CNVs with pathologic significance from normal variants. Together, this analysis and annotation provides a
useful resource to assist with the assessment of CNVs in the contexts of human variation, disease susceptibility, and clinical
molecular diagnostics. The CNV resource is available at: http://cnv.chop.edu.
Reprinted from Shaikh T., et al., High-Resolution Mapping and Analysis of Copy Number Variations in the Human Genome: A Data
Resource for Clinical and Research Applications Genome Research. 2009, with permission from Genome Research. CHOP CNVs from 2,026 disease-free individuals are available through dbVar at
http://www.ncbi.nlm.nih.gov/dbvar/studies/nstd21.
SECONDARY ACCESSION(S): PRJNA75523PRJNA75521
REPOSITORIES: dbGaP
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