Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Coulombe, Charles, Poitras, Christian, Nordell-Markovits, Alexei, Brunelle, Mylène, Lavoie, Marc-André, Robert, François, Jacques, Pierre-Étienne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
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
_version_ 1782324757921792000
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
work_keys_str_mv AT coulombecharles vapaversatileaggregateprofilerforefficientgenomewidedatarepresentationanddiscovery
AT poitraschristian vapaversatileaggregateprofilerforefficientgenomewidedatarepresentationanddiscovery
AT nordellmarkovitsalexei vapaversatileaggregateprofilerforefficientgenomewidedatarepresentationanddiscovery
AT brunellemylene vapaversatileaggregateprofilerforefficientgenomewidedatarepresentationanddiscovery
AT lavoiemarcandre vapaversatileaggregateprofilerforefficientgenomewidedatarepresentationanddiscovery
AT robertfrancois vapaversatileaggregateprofilerforefficientgenomewidedatarepresentationanddiscovery
AT jacquespierreetienne vapaversatileaggregateprofilerforefficientgenomewidedatarepresentationanddiscovery