CoNVaDING: Single Exon Variation Detection in Targeted NGS Data

Lennart Johansson(University Medical Center Groningen), Freerk van Dijk(University of Groningen), Eddy N. de Boer(University of Groningen), Krista K. van Dijk-Bos(University of Groningen), Jan D.H. Jongbloed(University of Groningen), Annemieke H. van der Hout(University Medical Center Groningen), Helga Westers(University of Groningen), Richard J. Sinke(University of Groningen), Morris A. Swertz(University Medical Center Groningen), Rolf H. Sijmons(University of Groningen), Birgit Sikkema‐Raddatz(University of Groningen)
Human Mutation
February 11, 2016
Cited by 97Open Access
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Abstract

We have developed a tool for detecting single exon copy-number variations (CNVs) in targeted next-generation sequencing data: CoNVaDING (Copy Number Variation Detection In Next-generation sequencing Gene panels). CoNVaDING includes a stringent quality control (QC) metric, that excludes or flags low-quality exons. Since this QC shows exactly which exons can be reliably analyzed and which exons are in need of an alternative analysis method, CoNVaDING is not only useful for CNV detection in a research setting, but also in clinical diagnostics. During the validation phase, CoNVaDING detected all known CNVs in high-quality targets in 320 samples analyzed, giving 100% sensitivity and 99.998% specificity for 308,574 exons. CoNVaDING outperforms existing tools by exhibiting a higher sensitivity and specificity and by precisely identifying low-quality samples and regions.


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