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Single-cell copy number variation detection

Detection of chromosomal aberrations from a single cell by array comparative genomic hybridization (single-cell array CGH), instead of from a population of cells, is an emerging technique. However, such detection is challenging because of the genome artifacts and the DNA amplification process inhere...

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Autores principales: Cheng, Jiqiu, Vanneste, Evelyne, Konings, Peter, Voet, Thierry, Vermeesch, Joris R, Moreau, Yves
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245619/
https://www.ncbi.nlm.nih.gov/pubmed/21854607
http://dx.doi.org/10.1186/gb-2011-12-8-r80
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author Cheng, Jiqiu
Vanneste, Evelyne
Konings, Peter
Voet, Thierry
Vermeesch, Joris R
Moreau, Yves
author_facet Cheng, Jiqiu
Vanneste, Evelyne
Konings, Peter
Voet, Thierry
Vermeesch, Joris R
Moreau, Yves
author_sort Cheng, Jiqiu
collection PubMed
description Detection of chromosomal aberrations from a single cell by array comparative genomic hybridization (single-cell array CGH), instead of from a population of cells, is an emerging technique. However, such detection is challenging because of the genome artifacts and the DNA amplification process inherent to the single cell approach. Current normalization algorithms result in inaccurate aberration detection for single-cell data. We propose a normalization method based on channel, genome composition and recurrent genome artifact corrections. We demonstrate that the proposed channel clone normalization significantly improves the copy number variation detection in both simulated and real single-cell array CGH data.
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spelling pubmed-32456192011-12-28 Single-cell copy number variation detection Cheng, Jiqiu Vanneste, Evelyne Konings, Peter Voet, Thierry Vermeesch, Joris R Moreau, Yves Genome Biol Method Detection of chromosomal aberrations from a single cell by array comparative genomic hybridization (single-cell array CGH), instead of from a population of cells, is an emerging technique. However, such detection is challenging because of the genome artifacts and the DNA amplification process inherent to the single cell approach. Current normalization algorithms result in inaccurate aberration detection for single-cell data. We propose a normalization method based on channel, genome composition and recurrent genome artifact corrections. We demonstrate that the proposed channel clone normalization significantly improves the copy number variation detection in both simulated and real single-cell array CGH data. BioMed Central 2011 2011-08-19 /pmc/articles/PMC3245619/ /pubmed/21854607 http://dx.doi.org/10.1186/gb-2011-12-8-r80 Text en Copyright ©2011 Cheng et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 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 cited.
spellingShingle Method
Cheng, Jiqiu
Vanneste, Evelyne
Konings, Peter
Voet, Thierry
Vermeesch, Joris R
Moreau, Yves
Single-cell copy number variation detection
title Single-cell copy number variation detection
title_full Single-cell copy number variation detection
title_fullStr Single-cell copy number variation detection
title_full_unstemmed Single-cell copy number variation detection
title_short Single-cell copy number variation detection
title_sort single-cell copy number variation detection
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245619/
https://www.ncbi.nlm.nih.gov/pubmed/21854607
http://dx.doi.org/10.1186/gb-2011-12-8-r80
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AT voetthierry singlecellcopynumbervariationdetection
AT vermeeschjorisr singlecellcopynumbervariationdetection
AT moreauyves singlecellcopynumbervariationdetection