M-CGH: Analysing microarray-based CGH experiments
<p>Abstract</p> <p>Background</p> <p>Microarray-based comparative genomic hybridisation (array CGH) is a technique by which variation in relative copy numbers between two genomes can be analysed by competitive hybridisation to DNA microarrays. This technology has most c...
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doaj-7a741b4618a9400e917a5ca62f0e99f42020-11-24T21:04:38ZengBMCBMC Bioinformatics1471-21052004-06-01517410.1186/1471-2105-5-74M-CGH: Analysing microarray-based CGH experimentsMeza-Zepeda Leonardo AWang JunbaiKresse Stine HMyklebost Ola<p>Abstract</p> <p>Background</p> <p>Microarray-based comparative genomic hybridisation (array CGH) is a technique by which variation in relative copy numbers between two genomes can be analysed by competitive hybridisation to DNA microarrays. This technology has most commonly been used to detect chromosomal amplifications and deletions in cancer. Dedicated tools are needed to analyse the results of such experiments, which include appropriate visualisation, and to take into consideration the physical relation in the genome between the probes on the array.</p> <p>Results</p> <p>M-CGH is a MATLAB toolbox with a graphical user interface designed specifically for the analysis of array CGH experiments, with multiple approaches to ratio normalization. Specifically, the distributions of three classes of DNA copy numbers (gains, normal and losses) can be estimated using a maximum likelihood method. Amplicon boundaries are computed by either the fuzzy K-nearest neighbour method or a wavelet approach. The program also allows linking each genomic clone with the corresponding genomic information in the Ensembl database <url>http://www.ensembl.org</url>.</p> <p>Conclusions</p> <p>M-CGH, which encompasses the basic tools needed for analysing array CGH experiments, is freely available for academics <url>http://www.uio.no/~junbaiw/mcgh</url>, and does not require any other MATLAB toolbox.</p> http://www.biomedcentral.com/1471-2105/5/74 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Meza-Zepeda Leonardo A Wang Junbai Kresse Stine H Myklebost Ola |
spellingShingle |
Meza-Zepeda Leonardo A Wang Junbai Kresse Stine H Myklebost Ola M-CGH: Analysing microarray-based CGH experiments BMC Bioinformatics |
author_facet |
Meza-Zepeda Leonardo A Wang Junbai Kresse Stine H Myklebost Ola |
author_sort |
Meza-Zepeda Leonardo A |
title |
M-CGH: Analysing microarray-based CGH experiments |
title_short |
M-CGH: Analysing microarray-based CGH experiments |
title_full |
M-CGH: Analysing microarray-based CGH experiments |
title_fullStr |
M-CGH: Analysing microarray-based CGH experiments |
title_full_unstemmed |
M-CGH: Analysing microarray-based CGH experiments |
title_sort |
m-cgh: analysing microarray-based cgh experiments |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2004-06-01 |
description |
<p>Abstract</p> <p>Background</p> <p>Microarray-based comparative genomic hybridisation (array CGH) is a technique by which variation in relative copy numbers between two genomes can be analysed by competitive hybridisation to DNA microarrays. This technology has most commonly been used to detect chromosomal amplifications and deletions in cancer. Dedicated tools are needed to analyse the results of such experiments, which include appropriate visualisation, and to take into consideration the physical relation in the genome between the probes on the array.</p> <p>Results</p> <p>M-CGH is a MATLAB toolbox with a graphical user interface designed specifically for the analysis of array CGH experiments, with multiple approaches to ratio normalization. Specifically, the distributions of three classes of DNA copy numbers (gains, normal and losses) can be estimated using a maximum likelihood method. Amplicon boundaries are computed by either the fuzzy K-nearest neighbour method or a wavelet approach. The program also allows linking each genomic clone with the corresponding genomic information in the Ensembl database <url>http://www.ensembl.org</url>.</p> <p>Conclusions</p> <p>M-CGH, which encompasses the basic tools needed for analysing array CGH experiments, is freely available for academics <url>http://www.uio.no/~junbaiw/mcgh</url>, and does not require any other MATLAB toolbox.</p> |
url |
http://www.biomedcentral.com/1471-2105/5/74 |
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