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SpeCond: a method to detect condition-specific gene expression
Transcriptomic studies routinely measure expression levels across numerous conditions. These datasets allow identification of genes that are specifically expressed in a small number of conditions. However, there are currently no statistically robust methods for identifying such genes. Here we presen...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3333772/ https://www.ncbi.nlm.nih.gov/pubmed/22008066 http://dx.doi.org/10.1186/gb-2011-12-10-r101 |
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author | Cavalli, Florence MG Bourgon, Richard Huber, Wolfgang Vaquerizas, Juan M Luscombe, Nicholas M |
author_facet | Cavalli, Florence MG Bourgon, Richard Huber, Wolfgang Vaquerizas, Juan M Luscombe, Nicholas M |
author_sort | Cavalli, Florence MG |
collection | PubMed |
description | Transcriptomic studies routinely measure expression levels across numerous conditions. These datasets allow identification of genes that are specifically expressed in a small number of conditions. However, there are currently no statistically robust methods for identifying such genes. Here we present SpeCond, a method to detect condition-specific genes that outperforms alternative approaches. We apply the method to a dataset of 32 human tissues to determine 2,673 specifically expressed genes. An implementation of SpeCond is freely available as a Bioconductor package at http://www.bioconductor.org/packages/release/bioc/html/SpeCond.html. |
format | Online Article Text |
id | pubmed-3333772 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-33337722012-04-23 SpeCond: a method to detect condition-specific gene expression Cavalli, Florence MG Bourgon, Richard Huber, Wolfgang Vaquerizas, Juan M Luscombe, Nicholas M Genome Biol Method Transcriptomic studies routinely measure expression levels across numerous conditions. These datasets allow identification of genes that are specifically expressed in a small number of conditions. However, there are currently no statistically robust methods for identifying such genes. Here we present SpeCond, a method to detect condition-specific genes that outperforms alternative approaches. We apply the method to a dataset of 32 human tissues to determine 2,673 specifically expressed genes. An implementation of SpeCond is freely available as a Bioconductor package at http://www.bioconductor.org/packages/release/bioc/html/SpeCond.html. BioMed Central 2011 2011-10-18 /pmc/articles/PMC3333772/ /pubmed/22008066 http://dx.doi.org/10.1186/gb-2011-12-10-r101 Text en Copyright ©2011 Cavalli 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 Cavalli, Florence MG Bourgon, Richard Huber, Wolfgang Vaquerizas, Juan M Luscombe, Nicholas M SpeCond: a method to detect condition-specific gene expression |
title | SpeCond: a method to detect condition-specific gene expression |
title_full | SpeCond: a method to detect condition-specific gene expression |
title_fullStr | SpeCond: a method to detect condition-specific gene expression |
title_full_unstemmed | SpeCond: a method to detect condition-specific gene expression |
title_short | SpeCond: a method to detect condition-specific gene expression |
title_sort | specond: a method to detect condition-specific gene expression |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3333772/ https://www.ncbi.nlm.nih.gov/pubmed/22008066 http://dx.doi.org/10.1186/gb-2011-12-10-r101 |
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