cnvHiTSeq: integrative models for high-resolution copy number variation detection and genotyping using population sequencing data
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 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
Bellos, Evangelos
719c8ef8-c89d-4231-810a-867dd59d31dc
Johnson, Michael R
6c920e81-43bd-4ae6-9d54-c6d2f55e3568
Coin, Lachlan J M
13d30334-d3b9-461e-b5e7-58fcbeff4db2
22 December 2012
Bellos, Evangelos
719c8ef8-c89d-4231-810a-867dd59d31dc
Johnson, Michael R
6c920e81-43bd-4ae6-9d54-c6d2f55e3568
Coin, Lachlan J M
13d30334-d3b9-461e-b5e7-58fcbeff4db2
Bellos, Evangelos, Johnson, Michael R and Coin, Lachlan J M
(2012)
cnvHiTSeq: integrative models for high-resolution copy number variation detection and genotyping using population sequencing data.
Genome Biology.
(doi:10.1186/gb-2012-13-12-r120).
Abstract
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
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Published date: 22 December 2012
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Local EPrints ID: 500667
URI: http://eprints.soton.ac.uk/id/eprint/500667
ISSN: 1465-6906
PURE UUID: a73ac2b6-0dfe-4bd7-b903-da0210bd79b7
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Date deposited: 08 May 2025 17:04
Last modified: 09 May 2025 02:14
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Author:
Evangelos Bellos
Author:
Michael R Johnson
Author:
Lachlan J M Coin
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