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cnvOffSeq: detecting intergenic copy number variation using off-target exome sequencing data
Motivation: Exome sequencing technologies have transformed the field of Mendelian genetics and allowed for efficient detection of genomic variants in protein-coding regions. The target enrichment process that is intrinsic to exome sequencing is inherently imperfect, generating large amounts of unint...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147927/ https://www.ncbi.nlm.nih.gov/pubmed/25161258 http://dx.doi.org/10.1093/bioinformatics/btu475 |
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author | Bellos, Evangelos Coin, Lachlan J. M. |
author_facet | Bellos, Evangelos Coin, Lachlan J. M. |
author_sort | Bellos, Evangelos |
collection | PubMed |
description | Motivation: Exome sequencing technologies have transformed the field of Mendelian genetics and allowed for efficient detection of genomic variants in protein-coding regions. The target enrichment process that is intrinsic to exome sequencing is inherently imperfect, generating large amounts of unintended off-target sequence. Off-target data are characterized by very low and highly heterogeneous coverage and are usually discarded by exome analysis pipelines. We posit that off-target read depth is a rich, but overlooked, source of information that could be mined to detect intergenic copy number variation (CNV). We propose cnvOffseq, a novel normalization framework for off-target read depth that is based on local adaptive singular value decomposition (SVD). This method is designed to address the heterogeneity of the underlying data and allows for accurate and precise CNV detection and genotyping in off-target regions. Results: cnvOffSeq was benchmarked on whole-exome sequencing samples from the 1000 Genomes Project. In a set of 104 gold standard intergenic deletions, our method achieved a sensitivity of 57.5% and a specificity of 99.2%, while maintaining a low FDR of 5%. For gold standard deletions longer than 5 kb, cnvOffSeq achieves a sensitivity of 90.4% without increasing the FDR. cnvOffSeq outperforms both whole-genome and whole-exome CNV detection methods considerably and is shown to offer a substantial improvement over naïve local SVD. Availability and Implementation: cnvOffSeq is available at http://sourceforge.net/p/cnvoffseq/ Contact: evangelos.bellos09@imperial.ac.uk or l.coin@imb.uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-4147927 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-41479272014-09-02 cnvOffSeq: detecting intergenic copy number variation using off-target exome sequencing data Bellos, Evangelos Coin, Lachlan J. M. Bioinformatics Eccb 2014 Proceedings Papers Committee Motivation: Exome sequencing technologies have transformed the field of Mendelian genetics and allowed for efficient detection of genomic variants in protein-coding regions. The target enrichment process that is intrinsic to exome sequencing is inherently imperfect, generating large amounts of unintended off-target sequence. Off-target data are characterized by very low and highly heterogeneous coverage and are usually discarded by exome analysis pipelines. We posit that off-target read depth is a rich, but overlooked, source of information that could be mined to detect intergenic copy number variation (CNV). We propose cnvOffseq, a novel normalization framework for off-target read depth that is based on local adaptive singular value decomposition (SVD). This method is designed to address the heterogeneity of the underlying data and allows for accurate and precise CNV detection and genotyping in off-target regions. Results: cnvOffSeq was benchmarked on whole-exome sequencing samples from the 1000 Genomes Project. In a set of 104 gold standard intergenic deletions, our method achieved a sensitivity of 57.5% and a specificity of 99.2%, while maintaining a low FDR of 5%. For gold standard deletions longer than 5 kb, cnvOffSeq achieves a sensitivity of 90.4% without increasing the FDR. cnvOffSeq outperforms both whole-genome and whole-exome CNV detection methods considerably and is shown to offer a substantial improvement over naïve local SVD. Availability and Implementation: cnvOffSeq is available at http://sourceforge.net/p/cnvoffseq/ Contact: evangelos.bellos09@imperial.ac.uk or l.coin@imb.uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2014-09-01 2014-08-22 /pmc/articles/PMC4147927/ /pubmed/25161258 http://dx.doi.org/10.1093/bioinformatics/btu475 Text en © The Author 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Eccb 2014 Proceedings Papers Committee Bellos, Evangelos Coin, Lachlan J. M. cnvOffSeq: detecting intergenic copy number variation using off-target exome sequencing data |
title | cnvOffSeq: detecting intergenic copy number variation using off-target exome sequencing data |
title_full | cnvOffSeq: detecting intergenic copy number variation using off-target exome sequencing data |
title_fullStr | cnvOffSeq: detecting intergenic copy number variation using off-target exome sequencing data |
title_full_unstemmed | cnvOffSeq: detecting intergenic copy number variation using off-target exome sequencing data |
title_short | cnvOffSeq: detecting intergenic copy number variation using off-target exome sequencing data |
title_sort | cnvoffseq: detecting intergenic copy number variation using off-target exome sequencing data |
topic | Eccb 2014 Proceedings Papers Committee |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147927/ https://www.ncbi.nlm.nih.gov/pubmed/25161258 http://dx.doi.org/10.1093/bioinformatics/btu475 |
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