New quality measure for SNP array based CNV detection.

Détails

ID Serval
serval:BIB_ACB3FE673051
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
New quality measure for SNP array based CNV detection.
Périodique
Bioinformatics (Oxford, England)
Auteur(s)
Macé A., Tuke M.A., Beckmann J.S., Lin L., Jacquemont S., Weedon M.N., Reymond A., Kutalik Z.
ISSN
1367-4811 (Electronic)
ISSN-L
1367-4803
Statut éditorial
Publié
Date de publication
01/11/2016
Peer-reviewed
Oui
Volume
32
Numéro
21
Pages
3298-3305
Langue
anglais
Notes
Publication types: Journal Article

Résumé
Only a few large systematic studies have evaluated the impact of copy number variants (CNVs) on common diseases. Several million individuals have been genotyped on single nucleotide variation arrays, which could be used for genome-wide CNVs association studies. However, CNV calls remain prone to false positives and only empirical filtering strategies exist in the literature. To overcome this issue, we defined a new quality score (QS) estimating the probability of a CNV called by PennCNV to be confirmed by other software.
Out-of-sample comparison showed that the correlation between the consensus CNV status and the QS is twice as high as it is for any previously proposed CNV filters. ROC curves displayed an AUC higher than 0.8 and simulations showed an increase up to 20% in statistical power when using QS in comparison to other filtering strategies. Superior performance was confirmed also for alternative consensus CNV definition and through improving known CNV-trait associations.
http://goo.gl/T6yuFM CONTACT: zoltan.kutalik@unil.ch or aurelien@mace@unil.chSupplementary information: Supplementary data are available at Bioinformatics online.

Pubmed
Open Access
Oui
Création de la notice
02/08/2016 11:02
Dernière modification de la notice
08/05/2019 23:37
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