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ToPASeq: an R package for topology-based pathway analysis of microarray and RNA-Seq data

BACKGROUND: Pathway analysis methods, in which differentially expressed genes are mapped to databases of reference pathways and relative enrichment is assessed, help investigators to propose biologically relevant hypotheses. The last generation of pathway analysis methods takes into account the topo...

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Autores principales: Ihnatova, Ivana, Budinska, Eva
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4625615/
https://www.ncbi.nlm.nih.gov/pubmed/26514335
http://dx.doi.org/10.1186/s12859-015-0763-1
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author Ihnatova, Ivana
Budinska, Eva
author_facet Ihnatova, Ivana
Budinska, Eva
author_sort Ihnatova, Ivana
collection PubMed
description BACKGROUND: Pathway analysis methods, in which differentially expressed genes are mapped to databases of reference pathways and relative enrichment is assessed, help investigators to propose biologically relevant hypotheses. The last generation of pathway analysis methods takes into account the topological structure of a pathway, which helps to increase both specificity and sensitivity of the findings. Simultaneously, the RNA-Seq technology is gaining popularity and becomes widely used for gene expression profiling. Unfortunately, majority of topological pathway analysis methods remains without implementation and if an implementation exists, it is limited in various factors. RESULTS: We developed a new R/Bioconductor package ToPASeq offering uniform interface to seven distinct topology-based pathway analysis methods, of which three we implemented de-novo and four were adjusted from existing implementations. Apart this, ToPASeq offers a set of tailored visualization functions and functions for importing and manipulating pathways and their topologies, facilitating the application of the methods on different species. The package can be used to compare the differential expression of pathways between two conditions on both gene expression microarray and RNA-Seq data. The package is written in R and is available from Bioconductor 3.2 using AGPL-3 license. CONCLUSION: ToPASeq is a novel package that offers seven distinct methods for topology-based pathway analysis, which are easily applicable on microarray as well as RNA-Seq data, both in human and other species. At the same time, it provides specific tools for visualization of the results. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0763-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-46256152015-10-30 ToPASeq: an R package for topology-based pathway analysis of microarray and RNA-Seq data Ihnatova, Ivana Budinska, Eva BMC Bioinformatics Software BACKGROUND: Pathway analysis methods, in which differentially expressed genes are mapped to databases of reference pathways and relative enrichment is assessed, help investigators to propose biologically relevant hypotheses. The last generation of pathway analysis methods takes into account the topological structure of a pathway, which helps to increase both specificity and sensitivity of the findings. Simultaneously, the RNA-Seq technology is gaining popularity and becomes widely used for gene expression profiling. Unfortunately, majority of topological pathway analysis methods remains without implementation and if an implementation exists, it is limited in various factors. RESULTS: We developed a new R/Bioconductor package ToPASeq offering uniform interface to seven distinct topology-based pathway analysis methods, of which three we implemented de-novo and four were adjusted from existing implementations. Apart this, ToPASeq offers a set of tailored visualization functions and functions for importing and manipulating pathways and their topologies, facilitating the application of the methods on different species. The package can be used to compare the differential expression of pathways between two conditions on both gene expression microarray and RNA-Seq data. The package is written in R and is available from Bioconductor 3.2 using AGPL-3 license. CONCLUSION: ToPASeq is a novel package that offers seven distinct methods for topology-based pathway analysis, which are easily applicable on microarray as well as RNA-Seq data, both in human and other species. At the same time, it provides specific tools for visualization of the results. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0763-1) contains supplementary material, which is available to authorized users. BioMed Central 2015-10-29 /pmc/articles/PMC4625615/ /pubmed/26514335 http://dx.doi.org/10.1186/s12859-015-0763-1 Text en © Ihnatova and Budinska. 2015 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Ihnatova, Ivana
Budinska, Eva
ToPASeq: an R package for topology-based pathway analysis of microarray and RNA-Seq data
title ToPASeq: an R package for topology-based pathway analysis of microarray and RNA-Seq data
title_full ToPASeq: an R package for topology-based pathway analysis of microarray and RNA-Seq data
title_fullStr ToPASeq: an R package for topology-based pathway analysis of microarray and RNA-Seq data
title_full_unstemmed ToPASeq: an R package for topology-based pathway analysis of microarray and RNA-Seq data
title_short ToPASeq: an R package for topology-based pathway analysis of microarray and RNA-Seq data
title_sort topaseq: an r package for topology-based pathway analysis of microarray and rna-seq data
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4625615/
https://www.ncbi.nlm.nih.gov/pubmed/26514335
http://dx.doi.org/10.1186/s12859-015-0763-1
work_keys_str_mv AT ihnatovaivana topaseqanrpackagefortopologybasedpathwayanalysisofmicroarrayandrnaseqdata
AT budinskaeva topaseqanrpackagefortopologybasedpathwayanalysisofmicroarrayandrnaseqdata