CoNVaDING: single exon variation detection in targeted NGS data: Single Exon Variation Detection in Targeted NGS Data

Lennart F Johansson, Freerk van Dijk, Eddy N de Boer, Krista K van Dijk-Bos, Jan DH Jongbloed, Annemieke H van der Hout, Helga Westers, Richard J Sinke, Morris A Swertz, Rolf H Sijmons

Onderzoeksoutput: Bijdrage aan tijdschriftArtikelpeer review

73 Citaten (Scopus)

Samenvatting

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. 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 metric, that excludes or flags low quality exons. Since this quality control shows exactly which exons can be reliably analysed and which exons are in need of an alternative analysis method, CoNVaDING is also useful for CNV detection in clinical diagnostics.

Originele taal-2Ongedefinieerd/onbekend
Pagina's (van-tot)457-464
Aantal pagina's8
TijdschriftHuman mutation
Volume37
Nummer van het tijdschrift5
DOI's
StatusGepubliceerd - 2016
Extern gepubliceerdJa

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