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VAP: a versatile aggregate profiler for efficient genome-wide data representation and discovery
The analysis of genomic data such as ChIP-Seq usually involves representing the signal intensity level over genes or other genetic features. This is often illustrated as a curve (representing the aggregate profile of a group of genes) or as a heatmap (representing individual genes). However, no spec...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086060/ https://www.ncbi.nlm.nih.gov/pubmed/24753414 http://dx.doi.org/10.1093/nar/gku302 |
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author | Coulombe, Charles Poitras, Christian Nordell-Markovits, Alexei Brunelle, Mylène Lavoie, Marc-André Robert, François Jacques, Pierre-Étienne |
author_facet | Coulombe, Charles Poitras, Christian Nordell-Markovits, Alexei Brunelle, Mylène Lavoie, Marc-André Robert, François Jacques, Pierre-Étienne |
author_sort | Coulombe, Charles |
collection | PubMed |
description | The analysis of genomic data such as ChIP-Seq usually involves representing the signal intensity level over genes or other genetic features. This is often illustrated as a curve (representing the aggregate profile of a group of genes) or as a heatmap (representing individual genes). However, no specific resource dedicated to easily generating such profiles is currently available. We therefore built the versatile aggregate profiler (VAP), designed to be used by experimental and computational biologists to generate profiles of genomic datasets over groups of regions of interest, using either an absolute or a relative method. Graphical representation of the results is automatically generated, and subgrouping can be performed easily, based on the orientation of the flanking annotations. The outputs include statistical measures to facilitate comparisons between groups or datasets. We show that, through its intuitive design and flexibility, VAP can help avoid misinterpretations of genomics data. VAP is highly efficient and designed to run on laptop computers by using a memory footprint control, but can also be easily compiled and run on servers. VAP is accessible at http://lab-jacques.recherche.usherbrooke.ca/vap/. |
format | Online Article Text |
id | pubmed-4086060 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-40860602014-12-02 VAP: a versatile aggregate profiler for efficient genome-wide data representation and discovery Coulombe, Charles Poitras, Christian Nordell-Markovits, Alexei Brunelle, Mylène Lavoie, Marc-André Robert, François Jacques, Pierre-Étienne Nucleic Acids Res Article The analysis of genomic data such as ChIP-Seq usually involves representing the signal intensity level over genes or other genetic features. This is often illustrated as a curve (representing the aggregate profile of a group of genes) or as a heatmap (representing individual genes). However, no specific resource dedicated to easily generating such profiles is currently available. We therefore built the versatile aggregate profiler (VAP), designed to be used by experimental and computational biologists to generate profiles of genomic datasets over groups of regions of interest, using either an absolute or a relative method. Graphical representation of the results is automatically generated, and subgrouping can be performed easily, based on the orientation of the flanking annotations. The outputs include statistical measures to facilitate comparisons between groups or datasets. We show that, through its intuitive design and flexibility, VAP can help avoid misinterpretations of genomics data. VAP is highly efficient and designed to run on laptop computers by using a memory footprint control, but can also be easily compiled and run on servers. VAP is accessible at http://lab-jacques.recherche.usherbrooke.ca/vap/. Oxford University Press 2014-07-01 2014-04-21 /pmc/articles/PMC4086060/ /pubmed/24753414 http://dx.doi.org/10.1093/nar/gku302 Text en © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Article Coulombe, Charles Poitras, Christian Nordell-Markovits, Alexei Brunelle, Mylène Lavoie, Marc-André Robert, François Jacques, Pierre-Étienne VAP: a versatile aggregate profiler for efficient genome-wide data representation and discovery |
title | VAP: a versatile aggregate profiler for efficient genome-wide data
representation and discovery |
title_full | VAP: a versatile aggregate profiler for efficient genome-wide data
representation and discovery |
title_fullStr | VAP: a versatile aggregate profiler for efficient genome-wide data
representation and discovery |
title_full_unstemmed | VAP: a versatile aggregate profiler for efficient genome-wide data
representation and discovery |
title_short | VAP: a versatile aggregate profiler for efficient genome-wide data
representation and discovery |
title_sort | vap: a versatile aggregate profiler for efficient genome-wide data
representation and discovery |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086060/ https://www.ncbi.nlm.nih.gov/pubmed/24753414 http://dx.doi.org/10.1093/nar/gku302 |
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