Performance assessment of copy number microarray platforms using a spike-in experiment | Zendy

Eitan Halper-Stromberg | Zendy; Laurence P. Frelin | Zendy; Ingo Ruczinski | Zendy; Robert B. Scharpf | Zendy; Chunfa Jie | Zendy; Benilton S. Carvalho | Zendy; Haiping Hao | Zendy; Kurt N. Hetrick | Zendy; Anne Jedlicka | Zendy; Amanda Dziedzic | Zendy; Kim Doheny | Zendy; Alan F. Scott | Zendy; Steve Baylin | Zendy; Jonathan Pevsner | Zendy; Forrest Spencer | Zendy; Rafael A. Irizarry | Zendy

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Performance assessment of copy number microarray platforms using a spike-in experiment

Author(s) -

Eitan Halper-Stromberg,

Laurence P. Frelin,

Ingo Ruczinski,

Robert B. Scharpf,

Chunfa Jie,

Benilton S. Carvalho,

Haiping Hao,

Kurt N. Hetrick,

Anne Jedlicka,

Amanda Dziedzic,

Kim Doheny,

Alan F. Scott,

Steve Baylin,

Jonathan Pevsner,

Forrest Spencer,

Rafael A. Irizarry

Publication year - 2011

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btr106

Subject(s) - copy number variation , computer science , pipeline (software) , leverage (statistics) , computational biology , r package , data mining , biology , genetics , genome , gene , artificial intelligence , programming language , computational science

Changes in the copy number of chromosomal DNA segments [copy number variants (CNVs)] have been implicated in human variation, heritable diseases and cancers. Microarray-based platforms are the current established technology of choice for studies reporting these discoveries and constitute the benchmark against which emergent sequence-based approaches will be evaluated. Research that depends on CNV analysis is rapidly increasing, and systematic platform assessments that distinguish strengths and weaknesses are needed to guide informed choice.

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