RT Journal
A1 Shaikh, Tamim H.
A1 Gai, Xiaowu
A1 Perin, Juan C.
A1 Glessner, Joseph T.
A1 Xie, Hongbo
A1 Murphy, Kevin
A1 O'Hara, Ryan
A1 Casalunovo, Tracy
A1 Conlin, Laura K.
A1 D'Arcy, Monica
A1 Frackelton, Edward C.
A1 Geiger, Elizabeth A.
A1 Haldeman-Englert, Chad
A1 Imielinski, Marcin
A1 Kim, Cecilia E.
A1 Medne, Livija
A1 Annaiah, Kiran
A1 Bradfield, Jonathan P.
A1 Dabaghyan, Elvira
A1 Eckert, Andrew
A1 Onyiah, Chioma C.
A1 Ostapenko, Svetlana
A1 Otieno, F. George
A1 Santa, Erin
A1 Shaner, Julie L.
A1 Skraban, Robert
A1 Smith, Ryan M.
A1 Elia, Josephine
A1 Goldmuntz, Elizabeth
A1 Spinner, Nancy B.
A1 Zackai, Elaine H.
A1 Chiavacci, Rosetta M.
A1 Grundmeier, Robert
A1 Rappaport, Eric F.
A1 Grant, Struan F.A.
A1 White, Peter S.
A1 Hakonarson, Hakon
T1 High-resolution mapping and analysis of copy number variations in the human genome: A data resource for clinical and research applications
JF Genome Research 
JO Genome Research 
YR 2009 
FD September 01 
VO 19 
IS 9 
SP 1682 
OP 1690 
DO 10.1101/gr.083501.108 
UL http://genome.cshlp.org/content/19/9/1682.abstract 
AB We present a database of copy number variations (CNVs) detected in 2026 disease-free individuals, using high-density, SNP-based oligonucleotide microarrays. This large cohort, comprised mainly of Caucasians (65.2%) and African-Americans (34.2%), was analyzed for CNVs in a single study using a uniform array platform and computational process. We have catalogued and characterized 54,462 individual CNVs, 77.8% of which were identified in multiple unrelated individuals. These nonunique CNVs mapped to 3272 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.