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Png, G.
; Suveges, D.* ; Park, Y.C.* ; Walter, K.* ; Kundu, K.* ; Ntalla, I.* ; Tsafantakis, E.* ; Karaleftheri, M.* ; Dedoussis, G.* ;
Zeggini, E.
;
Gilly, A.
Population-wide copy number variation calling using variant call format files from 6,898 individuals.
Genet. Epidemiol.
44
, 79-89 (2020)
Postprint
DOI
PMC
Open Access Green
möglich sobald bei der ZB eingereicht worden ist.
Abstract
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Zusatzinfos
© 2019 Wiley Periodicals, Inc. Copy number variants (CNVs) play an important role in a number of human diseases, but the accurate calling of CNVs remains challenging. Most current approaches to CNV detection use raw read alignments, which are computationally intensive to process. We use a regression tree-based approach to call germline CNVs from whole-genome sequencing (WGS, >18x) variant call sets in 6,898 samples across four European cohorts, and describe a rich large variation landscape comprising 1,320 CNVs. Eighty-one percent of detected events have been previously reported in the Database of Genomic Variants. Twenty-three percent of high-quality deletions affect entire genes, and we recapitulate known events such as the GSTM1 and RHD gene deletions. We test for association between the detected deletions and 275 protein levels in 1,457 individuals to assess the potential clinical impact of the detected CNVs. We describe complex CNV patterns underlying an association with levels of the CCL3 protein (MAF = 0.15, p = 3.6x10−12) at the CCL3L3 locus, and a novel cis-association between a low-frequency NOMO1 deletion and NOMO1 protein levels (MAF = 0.02, p = 2.2x10−7). This study demonstrates that existing population-wide WGS call sets can be mined for germline CNVs with minimal computational overhead, delivering insight into a less well-studied, yet potentially impactful class of genetic variant.
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Typ der Hochschulschrift
Herausgeber
Korrespondenzautor
Schlagwörter
Association Study ; Copy-number Variant ; Whole-genome Sequencing
Keywords plus
ISSN (print) / ISBN
0741-0395
e-ISSN
1098-2272
ISBN
Bandtitel
Konferenztitel
Konferzenzdatum
Konferenzort
Konferenzband
Zeitschrift
Genetic Epidemiology
Quellenangaben
Band: 44,
Heft: 1,
Seiten: 79-89
Artikelnummer: ,
Supplement: ,
Reihe
Verlag
Wiley
Verlagsort
Hochschule
Hochschulort
Fakultät
Veröffentlichungsdatum
0000-00-00
Veröffentlichungsnummer
Anmeldedatum
0000-00-00
Anmelder/Inhaber
weitere Inhaber
Anmeldeland
Priorität
Nichtpatentliteratur
Publikationen
Begutachtungsstatus
Peer reviewed
Institut(e)
Institute of Translational Genomics (ITG)
Förderungen