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Rapid Visualisation of Microarray Copy Number Data for the Detection of Structural Variations Linked to a Disease Phenotype
Whilst the majority of inherited diseases have been found to be caused by single base substitutions, small insertions or deletions (<1Kb), a significant proportion of genetic variability is due to copy number variation (CNV). The possible role of CNV in monogenic and complex diseases has recently...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3422275/ https://www.ncbi.nlm.nih.gov/pubmed/22912880 http://dx.doi.org/10.1371/journal.pone.0043466 |
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author | Carr, Ian M. Diggle, Christine P. Khan, Kamron Inglehearn, Chris McKibbin, Martin Bonthron, David T. Markham, Alexander F. Anwar, Rashida Dobbie, Angus Pena, Sergio D.J. Ali, Manir |
author_facet | Carr, Ian M. Diggle, Christine P. Khan, Kamron Inglehearn, Chris McKibbin, Martin Bonthron, David T. Markham, Alexander F. Anwar, Rashida Dobbie, Angus Pena, Sergio D.J. Ali, Manir |
author_sort | Carr, Ian M. |
collection | PubMed |
description | Whilst the majority of inherited diseases have been found to be caused by single base substitutions, small insertions or deletions (<1Kb), a significant proportion of genetic variability is due to copy number variation (CNV). The possible role of CNV in monogenic and complex diseases has recently attracted considerable interest. However, until the development of whole genome, oligonucleotide micro-arrays, designed specifically to detect the presence of copy number variation, it was not easy to screen an individual for the presence of unknown deletions or duplications with sizes below the level of sensitivity of optical microscopy (3–5 Mb). Now that currently available oligonucleotide micro-arrays have in excess of a million probes, the problem of copy number analysis has moved from one of data production to that of data analysis. We have developed CNViewer, to identify copy number variation that co-segregates with a disease phenotype in small nuclear families, from genome-wide oligonucleotide micro-array data. This freely available program should constitute a useful addition to the diagnostic armamentarium of clinical geneticists. |
format | Online Article Text |
id | pubmed-3422275 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-34222752012-08-21 Rapid Visualisation of Microarray Copy Number Data for the Detection of Structural Variations Linked to a Disease Phenotype Carr, Ian M. Diggle, Christine P. Khan, Kamron Inglehearn, Chris McKibbin, Martin Bonthron, David T. Markham, Alexander F. Anwar, Rashida Dobbie, Angus Pena, Sergio D.J. Ali, Manir PLoS One Research Article Whilst the majority of inherited diseases have been found to be caused by single base substitutions, small insertions or deletions (<1Kb), a significant proportion of genetic variability is due to copy number variation (CNV). The possible role of CNV in monogenic and complex diseases has recently attracted considerable interest. However, until the development of whole genome, oligonucleotide micro-arrays, designed specifically to detect the presence of copy number variation, it was not easy to screen an individual for the presence of unknown deletions or duplications with sizes below the level of sensitivity of optical microscopy (3–5 Mb). Now that currently available oligonucleotide micro-arrays have in excess of a million probes, the problem of copy number analysis has moved from one of data production to that of data analysis. We have developed CNViewer, to identify copy number variation that co-segregates with a disease phenotype in small nuclear families, from genome-wide oligonucleotide micro-array data. This freely available program should constitute a useful addition to the diagnostic armamentarium of clinical geneticists. Public Library of Science 2012-08-17 /pmc/articles/PMC3422275/ /pubmed/22912880 http://dx.doi.org/10.1371/journal.pone.0043466 Text en © 2012 Carr et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Carr, Ian M. Diggle, Christine P. Khan, Kamron Inglehearn, Chris McKibbin, Martin Bonthron, David T. Markham, Alexander F. Anwar, Rashida Dobbie, Angus Pena, Sergio D.J. Ali, Manir Rapid Visualisation of Microarray Copy Number Data for the Detection of Structural Variations Linked to a Disease Phenotype |
title | Rapid Visualisation of Microarray Copy Number Data for the Detection of Structural Variations Linked to a Disease Phenotype |
title_full | Rapid Visualisation of Microarray Copy Number Data for the Detection of Structural Variations Linked to a Disease Phenotype |
title_fullStr | Rapid Visualisation of Microarray Copy Number Data for the Detection of Structural Variations Linked to a Disease Phenotype |
title_full_unstemmed | Rapid Visualisation of Microarray Copy Number Data for the Detection of Structural Variations Linked to a Disease Phenotype |
title_short | Rapid Visualisation of Microarray Copy Number Data for the Detection of Structural Variations Linked to a Disease Phenotype |
title_sort | rapid visualisation of microarray copy number data for the detection of structural variations linked to a disease phenotype |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3422275/ https://www.ncbi.nlm.nih.gov/pubmed/22912880 http://dx.doi.org/10.1371/journal.pone.0043466 |
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