cnvHiTSeq: integrative models for high-resolution copy number variation detection and genotyping using population sequencing data
Recent advances in sequencing technologies provide the means for identifying copy number variation (CNV) at an unprecedented resolution. A single next-generation sequencing experiment offers several features that can be used to detect CNV, yet current methods do not incorporate all available signatu...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4056371/ https://www.ncbi.nlm.nih.gov/pubmed/23259578 http://dx.doi.org/10.1186/gb-2012-13-12-r120 |
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author | Bellos, Evangelos Johnson, Michael R M Coin, Lachlan J |
author_facet | Bellos, Evangelos Johnson, Michael R M Coin, Lachlan J |
author_sort | Bellos, Evangelos |
collection | PubMed |
description | Recent advances in sequencing technologies provide the means for identifying copy number variation (CNV) at an unprecedented resolution. A single next-generation sequencing experiment offers several features that can be used to detect CNV, yet current methods do not incorporate all available signatures into a unified model. cnvHiTSeq is an integrative probabilistic method for CNV discovery and genotyping that jointly analyzes multiple features at the population level. By combining evidence from complementary sources, cnvHiTSeq achieves high genotyping accuracy and a substantial improvement in CNV detection sensitivity over existing methods, while maintaining a low false discovery rate. cnvHiTSeq is available at http://sourceforge.net/projects/cnvhitseq |
format | Online Article Text |
id | pubmed-4056371 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40563712014-06-13 cnvHiTSeq: integrative models for high-resolution copy number variation detection and genotyping using population sequencing data Bellos, Evangelos Johnson, Michael R M Coin, Lachlan J Genome Biol Method Recent advances in sequencing technologies provide the means for identifying copy number variation (CNV) at an unprecedented resolution. A single next-generation sequencing experiment offers several features that can be used to detect CNV, yet current methods do not incorporate all available signatures into a unified model. cnvHiTSeq is an integrative probabilistic method for CNV discovery and genotyping that jointly analyzes multiple features at the population level. By combining evidence from complementary sources, cnvHiTSeq achieves high genotyping accuracy and a substantial improvement in CNV detection sensitivity over existing methods, while maintaining a low false discovery rate. cnvHiTSeq is available at http://sourceforge.net/projects/cnvhitseq BioMed Central 2012 2012-12-22 /pmc/articles/PMC4056371/ /pubmed/23259578 http://dx.doi.org/10.1186/gb-2012-13-12-r120 Text en Copyright © 2013 Bellos et al.; licensee BioMed Central Ltd. |
spellingShingle | Method Bellos, Evangelos Johnson, Michael R M Coin, Lachlan J cnvHiTSeq: integrative models for high-resolution copy number variation detection and genotyping using population sequencing data |
title | cnvHiTSeq: integrative models for high-resolution copy number variation detection and genotyping using population sequencing data |
title_full | cnvHiTSeq: integrative models for high-resolution copy number variation detection and genotyping using population sequencing data |
title_fullStr | cnvHiTSeq: integrative models for high-resolution copy number variation detection and genotyping using population sequencing data |
title_full_unstemmed | cnvHiTSeq: integrative models for high-resolution copy number variation detection and genotyping using population sequencing data |
title_short | cnvHiTSeq: integrative models for high-resolution copy number variation detection and genotyping using population sequencing data |
title_sort | cnvhitseq: integrative models for high-resolution copy number variation detection and genotyping using population sequencing data |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4056371/ https://www.ncbi.nlm.nih.gov/pubmed/23259578 http://dx.doi.org/10.1186/gb-2012-13-12-r120 |
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