TY  - JOUR
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
Y1  - 2009/09/01 
JF  - Genome Research 
JO  - Genome Research 
SP  - 1682 
EP  - 1690 
DO  - 10.1101/gr.083501.108 
VL  - 19 
IS  - 9 
UR  - http://genome.cshlp.org/content/19/9/1682.abstract 
N2  - 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. 
ER  -