Human gene correlation analysis (HGCA): A tool for the identification of transcriptionally co-expressed genes
<p>Abstract</p> <p>Background</p> <p>Bioinformatics and high-throughput technologies such as microarray studies allow the measure of the expression levels of large numbers of genes simultaneously, thus helping us to understand the molecular mechanisms of various biologi...
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| Format: | Article |
| Language: | English |
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BMC
2012-06-01
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| Series: | BMC Research Notes |
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| Online Access: | http://www.biomedcentral.com/1756-0500/5/265 |
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| author | Michalopoulos Ioannis Pavlopoulos Georgios A Malatras Apostolos Karelas Alexandros Kostadima Myrto-Areti Schneider Reinhard Kossida Sophia |
| author_facet | Michalopoulos Ioannis Pavlopoulos Georgios A Malatras Apostolos Karelas Alexandros Kostadima Myrto-Areti Schneider Reinhard Kossida Sophia |
| author_sort | Michalopoulos Ioannis |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>Bioinformatics and high-throughput technologies such as microarray studies allow the measure of the expression levels of large numbers of genes simultaneously, thus helping us to understand the molecular mechanisms of various biological processes in a cell.</p> <p>Findings</p> <p>We calculate the Pearson Correlation Coefficient (<it>r-</it>value) between probe set signal values from Affymetrix Human Genome Microarray samples and cluster the human genes according to the <it>r-</it>value correlation matrix using the Neighbour Joining (NJ) clustering method. A hyper-geometric distribution is applied on the text annotations of the probe sets to quantify the term overrepresentations. The aim of the tool is the identification of closely correlated genes for a given gene of interest and/or the prediction of its biological function, which is based on the annotations of the respective gene cluster.</p> <p>Conclusion</p> <p><it>Human Gene Correlation Analysis</it> (HGCA) is a tool to classify human genes according to their coexpression levels and to identify overrepresented annotation terms in correlated gene groups. It is available at: <url>http://biobank-informatics.bioacademy.gr/coexpression/</url>.</p> |
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| format | Article |
| id | doaj.art-e4240e3a0da2431392f08ccda7c0a954 |
| institution | Directory Open Access Journal |
| issn | 1756-0500 |
| language | English |
| last_indexed | 2024-12-12T09:19:21Z |
| publishDate | 2012-06-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Research Notes |
| spelling | doaj.art-e4240e3a0da2431392f08ccda7c0a9542022-12-22T00:29:16ZengBMCBMC Research Notes1756-05002012-06-015126510.1186/1756-0500-5-265Human gene correlation analysis (HGCA): A tool for the identification of transcriptionally co-expressed genesMichalopoulos IoannisPavlopoulos Georgios AMalatras ApostolosKarelas AlexandrosKostadima Myrto-AretiSchneider ReinhardKossida Sophia<p>Abstract</p> <p>Background</p> <p>Bioinformatics and high-throughput technologies such as microarray studies allow the measure of the expression levels of large numbers of genes simultaneously, thus helping us to understand the molecular mechanisms of various biological processes in a cell.</p> <p>Findings</p> <p>We calculate the Pearson Correlation Coefficient (<it>r-</it>value) between probe set signal values from Affymetrix Human Genome Microarray samples and cluster the human genes according to the <it>r-</it>value correlation matrix using the Neighbour Joining (NJ) clustering method. A hyper-geometric distribution is applied on the text annotations of the probe sets to quantify the term overrepresentations. The aim of the tool is the identification of closely correlated genes for a given gene of interest and/or the prediction of its biological function, which is based on the annotations of the respective gene cluster.</p> <p>Conclusion</p> <p><it>Human Gene Correlation Analysis</it> (HGCA) is a tool to classify human genes according to their coexpression levels and to identify overrepresented annotation terms in correlated gene groups. It is available at: <url>http://biobank-informatics.bioacademy.gr/coexpression/</url>.</p>http://www.biomedcentral.com/1756-0500/5/265Microarray analysisGene annotationGene coexpressionFunctional annotation |
| spellingShingle | Michalopoulos Ioannis Pavlopoulos Georgios A Malatras Apostolos Karelas Alexandros Kostadima Myrto-Areti Schneider Reinhard Kossida Sophia Human gene correlation analysis (HGCA): A tool for the identification of transcriptionally co-expressed genes BMC Research Notes Microarray analysis Gene annotation Gene coexpression Functional annotation |
| title | Human gene correlation analysis (HGCA): A tool for the identification of transcriptionally co-expressed genes |
| title_full | Human gene correlation analysis (HGCA): A tool for the identification of transcriptionally co-expressed genes |
| title_fullStr | Human gene correlation analysis (HGCA): A tool for the identification of transcriptionally co-expressed genes |
| title_full_unstemmed | Human gene correlation analysis (HGCA): A tool for the identification of transcriptionally co-expressed genes |
| title_short | Human gene correlation analysis (HGCA): A tool for the identification of transcriptionally co-expressed genes |
| title_sort | human gene correlation analysis hgca a tool for the identification of transcriptionally co expressed genes |
| topic | Microarray analysis Gene annotation Gene coexpression Functional annotation |
| url | http://www.biomedcentral.com/1756-0500/5/265 |
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