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Allele-specific copy-number discovery from whole-genome and whole-exome sequencing
Copy-number variants (CNVs) are a major form of genetic variation and a risk factor for various human diseases, so it is crucial to accurately detect and characterize them. It is conceivable that allele-specific reads from high-throughput sequencing data could be leveraged to both enhance CNV detect...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4538801/ https://www.ncbi.nlm.nih.gov/pubmed/25883151 http://dx.doi.org/10.1093/nar/gkv319 |
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author | Wang, WeiBo Wang, Wei Sun, Wei Crowley, James J. Szatkiewicz, Jin P. |
author_facet | Wang, WeiBo Wang, Wei Sun, Wei Crowley, James J. Szatkiewicz, Jin P. |
author_sort | Wang, WeiBo |
collection | PubMed |
description | Copy-number variants (CNVs) are a major form of genetic variation and a risk factor for various human diseases, so it is crucial to accurately detect and characterize them. It is conceivable that allele-specific reads from high-throughput sequencing data could be leveraged to both enhance CNV detection and produce allele-specific copy number (ASCN) calls. Although statistical methods have been developed to detect CNVs using whole-genome sequence (WGS) and/or whole-exome sequence (WES) data, information from allele-specific read counts has not yet been adequately exploited. In this paper, we develop an integrated method, called AS-GENSENG, which incorporates allele-specific read counts in CNV detection and estimates ASCN using either WGS or WES data. To evaluate the performance of AS-GENSENG, we conducted extensive simulations, generated empirical data using existing WGS and WES data sets and validated predicted CNVs using an independent methodology. We conclude that AS-GENSENG not only predicts accurate ASCN calls but also improves the accuracy of total copy number calls, owing to its unique ability to exploit information from both total and allele-specific read counts while accounting for various experimental biases in sequence data. Our novel, user-friendly and computationally efficient method and a complete analytic protocol is freely available at https://sourceforge.net/projects/asgenseng/. |
format | Online Article Text |
id | pubmed-4538801 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-45388012015-08-18 Allele-specific copy-number discovery from whole-genome and whole-exome sequencing Wang, WeiBo Wang, Wei Sun, Wei Crowley, James J. Szatkiewicz, Jin P. Nucleic Acids Res Methods Online Copy-number variants (CNVs) are a major form of genetic variation and a risk factor for various human diseases, so it is crucial to accurately detect and characterize them. It is conceivable that allele-specific reads from high-throughput sequencing data could be leveraged to both enhance CNV detection and produce allele-specific copy number (ASCN) calls. Although statistical methods have been developed to detect CNVs using whole-genome sequence (WGS) and/or whole-exome sequence (WES) data, information from allele-specific read counts has not yet been adequately exploited. In this paper, we develop an integrated method, called AS-GENSENG, which incorporates allele-specific read counts in CNV detection and estimates ASCN using either WGS or WES data. To evaluate the performance of AS-GENSENG, we conducted extensive simulations, generated empirical data using existing WGS and WES data sets and validated predicted CNVs using an independent methodology. We conclude that AS-GENSENG not only predicts accurate ASCN calls but also improves the accuracy of total copy number calls, owing to its unique ability to exploit information from both total and allele-specific read counts while accounting for various experimental biases in sequence data. Our novel, user-friendly and computationally efficient method and a complete analytic protocol is freely available at https://sourceforge.net/projects/asgenseng/. Oxford University Press 2015-08-18 2015-04-16 /pmc/articles/PMC4538801/ /pubmed/25883151 http://dx.doi.org/10.1093/nar/gkv319 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Online Wang, WeiBo Wang, Wei Sun, Wei Crowley, James J. Szatkiewicz, Jin P. Allele-specific copy-number discovery from whole-genome and whole-exome sequencing |
title | Allele-specific copy-number discovery from whole-genome and whole-exome sequencing |
title_full | Allele-specific copy-number discovery from whole-genome and whole-exome sequencing |
title_fullStr | Allele-specific copy-number discovery from whole-genome and whole-exome sequencing |
title_full_unstemmed | Allele-specific copy-number discovery from whole-genome and whole-exome sequencing |
title_short | Allele-specific copy-number discovery from whole-genome and whole-exome sequencing |
title_sort | allele-specific copy-number discovery from whole-genome and whole-exome sequencing |
topic | Methods Online |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4538801/ https://www.ncbi.nlm.nih.gov/pubmed/25883151 http://dx.doi.org/10.1093/nar/gkv319 |
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