TY  - JOUR
A1  - Fiegler, Heike
A1  - Redon, Richard
A1  - Andrews, Dan
A1  - Scott, Carol
A1  - Andrews, Robert
A1  - Carder, Carol
A1  - Clark, Richard
A1  - Dovey, Oliver
A1  - Ellis, Peter
A1  - Feuk, Lars
A1  - French, Lisa
A1  - Hunt, Paul
A1  - Kalaitzopoulos, Dimitrios
A1  - Larkin, James
A1  - Montgomery, Lyndal
A1  - Perry, George H.
A1  - Plumb, Bob W.
A1  - Porter, Keith
A1  - Rigby, Rachel E.
A1  - Rigler, Diane
A1  - Valsesia, Armand
A1  - Langford, Cordelia
A1  - Humphray, Sean J.
A1  - Scherer, Stephen W.
A1  - Lee, Charles
A1  - Hurles, Matthew E.
A1  - Carter, Nigel P.
T1  - Accurate and reliable high-throughput detection of copy number variation in the human genome
Y1  - 2006/12/01 
JF  - Genome Research 
JO  - Genome Research 
SP  - 1566 
EP  - 1574 
DO  - 10.1101/gr.5630906 
VL  - 16 
IS  - 12 
UR  - http://genome.cshlp.org/content/16/12/1566.abstract 
N2  - This study describes a new tool for accurate and reliable high-throughput detection of copy number variation in the human genome. We have constructed a large-insert clone DNA microarray covering the entire human genome in tiling path resolution that we have used to identify copy number variation in human populations. Crucial to this study has been the development of a robust array platform and analytic process for the automated identification of copy number variants (CNVs). The array consists of 26,574 clones covering 93.7% of euchromatic regions. Clones were selected primarily from the published “Golden Path,” and mapping was confirmed by fingerprinting and BAC-end sequencing. Array performance was extensively tested by a series of validation assays. These included determining the hybridization characteristics of each individual clone on the array by chromosome-specific add-in experiments. Estimation of data reproducibility and false-positive/negative rates was carried out using self–self hybridizations, replicate experiments, and independent validations of CNVs. Based on these studies, we developed a variance-based automatic copy number detection analysis process (CNVfinder) and have demonstrated its robustness by comparison with the SW-ARRAY method. 
ER  -