An exome sequencing pipeline for identifying and genotyping common CNVs associated with disease with application to psoriasis

Coin, Lachlan J. M., Cao, Dandan, Ren, Jingjing, Zuo, Xianbo, Sun, Liangdan, Yang, Sen, Zhang, Xuejun, Cui, Yong, Li, Yingrui, Jin, Xin and Wang, Jun (2012) An exome sequencing pipeline for identifying and genotyping common CNVs associated with disease with application to psoriasis. Bioinformatics, 28 18: I370-I374. doi:10.1093/bioinformatics/bts379


Author Coin, Lachlan J. M.
Cao, Dandan
Ren, Jingjing
Zuo, Xianbo
Sun, Liangdan
Yang, Sen
Zhang, Xuejun
Cui, Yong
Li, Yingrui
Jin, Xin
Wang, Jun
Title An exome sequencing pipeline for identifying and genotyping common CNVs associated with disease with application to psoriasis
Journal name Bioinformatics   Check publisher's open access policy
ISSN 1367-4803
1367-4811
Publication date 2012
Sub-type Article (original research)
DOI 10.1093/bioinformatics/bts379
Open Access Status
Volume 28
Issue 18
Start page I370
End page I374
Total pages 5
Place of publication Oxford, United Kingdom
Publisher Oxford University Press
Language eng
Formatted abstract
Motivation: Despite the prevalence of copy number variation (CNV) in the human genome, only a handful of confirmed associations have been reported between common CNVs and complex disease. This may be partially attributed to the difficulty in accurately genotyping CNVs in large cohorts using array-based technologies. Exome sequencing is now widely being applied to case-control cohorts and presents an exciting opportunity to look for common CNVs associated with disease.

Results: We developed ExoCNVTest: an exome sequencing analysis pipeline to identify disease-associated CNVs and to generate absolute copy number genotypes at putatively associated loci. Our method re-discovered the LCE3B_LCE3C CNV association with psoriasis (P-value = 5 × 10e-6) while controlling inflation of test statistics (λ<1). ExoCNVTest-derived absolute CNV genotypes were 97.4% concordant with PCR-derived genotypes at this locus. 
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: Institute for Molecular Bioscience - Publications
 
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