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A high-resolution copy-number variation resource for clinical and population genetics
Author(s) -
Mohammed Uddin,
Bhooma Thiruvahindrapuram,
Susan Walker,
Zhuozhi Wang,
Pingzhao Hu,
Sylvia Lamoureux,
John Wei,
Jeffrey R. MacDonald,
Giovanna Pellecchia,
Chao Lu,
Anath C. Lionel,
Matthew J. Gazzellone,
John McLaughlin,
Catherine Brown,
Irene L. Andrulis,
Julia A. Knight,
Jo-Anne Herbrick,
Richard F. Wintle,
Peter N. Ray,
Dimitri J. Stavropoulos,
Christian R. Marshall,
Stephen W. Scherer
Publication year - 2014
Publication title -
genetics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.509
H-Index - 128
eISSN - 1530-0366
pISSN - 1098-3600
DOI - 10.1038/gim.2014.178
Subject(s) - copy number variation , genotyping , genetics , biology , population , population genomics , copy number analysis , medical genetics , genotype , genomics , computational biology , medicine , gene , genome , environmental health
Chromosomal microarray analysis to assess copy-number variation has become a first-tier genetic diagnostic test for individuals with unexplained neurodevelopmental disorders or multiple congenital anomalies. More than 100 cytogenetic laboratories worldwide use the new ultra-high resolution Affymetrix CytoScan-HD array to genotype hundreds of thousands of samples per year. Our aim was to develop a copy-number variation resource from a new population sample that would enable more accurate interpretation of clinical genetics data on this microarray platform and others.

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