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dc.contributor.authorÖzden, Furkan
dc.contributor.authorAlkan, Can
dc.contributor.authorÇiçek, A. Ercüment
dc.date.accessioned2023-02-27T20:21:48Z
dc.date.available2023-02-27T20:21:48Z
dc.date.issued2022-06-13
dc.identifier.issn1088-9051
dc.identifier.urihttp://hdl.handle.net/11693/111856
dc.description.abstractAccurate and efficient detection of copy number variants (CNVs) is of critical importance owing to their significant association with complex genetic diseases. Although algorithms that use whole-genome sequencing (WGS) data provide stable results with mostly valid statistical assumptions, copy number detection on whole-exome sequencing (WES) data shows comparatively lower accuracy. This is unfortunate as WES data are cost-efficient, compact, and relatively ubiquitous. The bottleneck is primarily due to the noncontiguous nature of the targeted capture: biases in targeted genomic hybridization, GC content, targeting probes, and sample batching during sequencing. Here, we present a novel deep learning model, DECoNT, which uses the matched WES and WGS data, and learns to correct the copy number variations reported by any off-the-shelf WES-based germline CNV caller. We train DECoNT on the 1000 Genomes Project data, and we show that we can efficiently triple the duplication call precision and double the deletion call precision of the state-of-the-art algorithms. We also show that our model consistently improves the performance independent of (1) sequencing technology, (2) exome capture kit, and (3) CNV caller. Using DECoNT as a universal exome CNV call polisher has the potential to improve the reliability of germline CNV detection on WES data sets. © 2022 Özden et al.; Published by Cold Spring Harbor Laboratory Press.en_US
dc.language.isoEnglishen_US
dc.source.titleGenome researchen_US
dc.relation.isversionofhttps://dx.doi.org/10.1101/gr.274845.120en_US
dc.titlePolishing copy number variant calls on exome sequencing data via deep learningen_US
dc.typeArticleen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.citation.spage1170en_US
dc.citation.epage1182en_US
dc.citation.volumeNumber32en_US
dc.citation.issueNumber6en_US
dc.identifier.doi10.1101/gr.274845.120en_US
dc.publisherNLM (Medline)en_US
dc.contributor.bilkentauthorÖzden, Furkan
dc.contributor.bilkentauthorAlkan, Can
dc.contributor.bilkentauthorÇiçek, A. Ercüment
dc.identifier.eissn1549-5469
buir.contributor.orcidAlkan, Can|0000-0002-5443-0706en_US
buir.contributor.orcidÇiçek, A. Ercüment|0000-0001-8613-6619en_US


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