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ClearCNV: CNV calling from NGS panel data in the presence of ambiguity and noise.
May, Vinzenz; Koch, Leonard; Fischer-Zirnsak, Björn; Horn, Denise; Gehle, Petra; Kornak, Uwe; Beule, Dieter; Holtgrewe, Manuel.
Afiliación
  • May V; Core Unit Bioinformatics (CUBI), Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin 10117, Germany.
  • Koch L; Institute of Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin 13353, Germany.
  • Fischer-Zirnsak B; Institute of Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin 13353, Germany.
  • Horn D; FG Development and Disease, Max-Planck-Institut für Molekulare Genetik, Berlin 14195, Germany.
  • Gehle P; Institute of Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin 13353, Germany.
  • Kornak U; Department of Internal Medicine-Cardiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin 13353, Germany.
  • Beule D; DZHK (German Center for Cardiovascular Research), Berlin, Germany.
  • Holtgrewe M; FG Development and Disease, Max-Planck-Institut für Molekulare Genetik, Berlin 14195, Germany.
Bioinformatics ; 38(16): 3871-3876, 2022 08 10.
Article en En | MEDLINE | ID: mdl-35751599
MOTIVATION: While the identification of small variants in panel sequencing data can be considered a solved problem, the identification of larger, multi-exon copy number variants (CNVs) still poses a considerable challenge. Thus, CNV calling has not been established in all laboratories performing panel sequencing. At the same time, such laboratories have accumulated large datasets and thus have the need to identify CNVs on their data to close the diagnostic gap. RESULTS: In this article, we present our method clearCNV that addresses this need in two ways. First, it helps laboratories to properly assign datasets to enrichment kits. Based on homogeneous subsets of data, clearCNV identifies CNVs affecting the targeted regions. Using real-world datasets and validation, we show that our method is highly competitive with previous methods and preferable in terms of specificity. AVAILABILITY AND IMPLEMENTATION: The software is available for free under a permissible license at https://github.com/bihealth/clear-cnv. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Variaciones en el Número de Copia de ADN Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Alemania

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Variaciones en el Número de Copia de ADN Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Alemania