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DB(2): a probabilistic approach for accurate detection of tandem duplication breakpoints using paired-end reads
BACKGROUND: With the advent of paired-end high throughput sequencing, it is now possible to identify various types of structural variation on a genome-wide scale. Although many methods have been proposed for structural variation detection, most do not provide precise boundaries for identified varian...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4234483/ https://www.ncbi.nlm.nih.gov/pubmed/24597945 http://dx.doi.org/10.1186/1471-2164-15-175 |
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author | Yavaş, Gökhan Koyutürk, Mehmet Gould, Meetha P McMahon, Sarah LaFramboise, Thomas |
author_facet | Yavaş, Gökhan Koyutürk, Mehmet Gould, Meetha P McMahon, Sarah LaFramboise, Thomas |
author_sort | Yavaş, Gökhan |
collection | PubMed |
description | BACKGROUND: With the advent of paired-end high throughput sequencing, it is now possible to identify various types of structural variation on a genome-wide scale. Although many methods have been proposed for structural variation detection, most do not provide precise boundaries for identified variants. In this paper, we propose a new method, Distribution Based detection of Duplication Boundaries (DB(2)), for accurate detection of tandem duplication breakpoints, an important class of structural variation, with high precision and recall. RESULTS: Our computational experiments on simulated data show that DB(2) outperforms state-of-the-art methods in terms of finding breakpoints of tandem duplications, with a higher positive predictive value (precision) in calling the duplications’ presence. In particular, DB(2)’s prediction of tandem duplications is correct 99% of the time even for very noisy data, while narrowing down the space of possible breakpoints within a margin of 15 to 20 bps on the average. Most of the existing methods provide boundaries in ranges that extend to hundreds of bases with lower precision values. Our method is also highly robust to varying properties of the sequencing library and to the sizes of the tandem duplications, as shown by its stable precision, recall and mean boundary mismatch performance. We demonstrate our method’s efficacy using both simulated paired-end reads, and those generated from a melanoma sample and two ovarian cancer samples. Newly discovered tandem duplications are validated using PCR and Sanger sequencing. CONCLUSIONS: Our method, DB(2), uses discordantly aligned reads, taking into account the distribution of fragment length to predict tandem duplications along with their breakpoints on a donor genome. The proposed method fine tunes the breakpoint calls by applying a novel probabilistic framework that incorporates the empirical fragment length distribution to score each feasible breakpoint. DB(2) is implemented in Java programming language and is freely available at http://mendel.gene.cwru.edu/laframboiselab/software.php. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2164-15-175) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4234483 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-42344832014-11-19 DB(2): a probabilistic approach for accurate detection of tandem duplication breakpoints using paired-end reads Yavaş, Gökhan Koyutürk, Mehmet Gould, Meetha P McMahon, Sarah LaFramboise, Thomas BMC Genomics Methodology Article BACKGROUND: With the advent of paired-end high throughput sequencing, it is now possible to identify various types of structural variation on a genome-wide scale. Although many methods have been proposed for structural variation detection, most do not provide precise boundaries for identified variants. In this paper, we propose a new method, Distribution Based detection of Duplication Boundaries (DB(2)), for accurate detection of tandem duplication breakpoints, an important class of structural variation, with high precision and recall. RESULTS: Our computational experiments on simulated data show that DB(2) outperforms state-of-the-art methods in terms of finding breakpoints of tandem duplications, with a higher positive predictive value (precision) in calling the duplications’ presence. In particular, DB(2)’s prediction of tandem duplications is correct 99% of the time even for very noisy data, while narrowing down the space of possible breakpoints within a margin of 15 to 20 bps on the average. Most of the existing methods provide boundaries in ranges that extend to hundreds of bases with lower precision values. Our method is also highly robust to varying properties of the sequencing library and to the sizes of the tandem duplications, as shown by its stable precision, recall and mean boundary mismatch performance. We demonstrate our method’s efficacy using both simulated paired-end reads, and those generated from a melanoma sample and two ovarian cancer samples. Newly discovered tandem duplications are validated using PCR and Sanger sequencing. CONCLUSIONS: Our method, DB(2), uses discordantly aligned reads, taking into account the distribution of fragment length to predict tandem duplications along with their breakpoints on a donor genome. The proposed method fine tunes the breakpoint calls by applying a novel probabilistic framework that incorporates the empirical fragment length distribution to score each feasible breakpoint. DB(2) is implemented in Java programming language and is freely available at http://mendel.gene.cwru.edu/laframboiselab/software.php. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2164-15-175) contains supplementary material, which is available to authorized users. BioMed Central 2014-03-05 /pmc/articles/PMC4234483/ /pubmed/24597945 http://dx.doi.org/10.1186/1471-2164-15-175 Text en © Yavaş et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. |
spellingShingle | Methodology Article Yavaş, Gökhan Koyutürk, Mehmet Gould, Meetha P McMahon, Sarah LaFramboise, Thomas DB(2): a probabilistic approach for accurate detection of tandem duplication breakpoints using paired-end reads |
title | DB(2): a probabilistic approach for accurate detection of tandem duplication breakpoints using paired-end reads |
title_full | DB(2): a probabilistic approach for accurate detection of tandem duplication breakpoints using paired-end reads |
title_fullStr | DB(2): a probabilistic approach for accurate detection of tandem duplication breakpoints using paired-end reads |
title_full_unstemmed | DB(2): a probabilistic approach for accurate detection of tandem duplication breakpoints using paired-end reads |
title_short | DB(2): a probabilistic approach for accurate detection of tandem duplication breakpoints using paired-end reads |
title_sort | db(2): a probabilistic approach for accurate detection of tandem duplication breakpoints using paired-end reads |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4234483/ https://www.ncbi.nlm.nih.gov/pubmed/24597945 http://dx.doi.org/10.1186/1471-2164-15-175 |
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