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ToPASeq: an R package for topology-based pathway analysis of microarray and RNA-Seq data
I. Ihnatova, E. Budinska,
Jazyk angličtina Země Anglie, Velká Británie
Typ dokumentu časopisecké články, práce podpořená grantem
NLK
BioMedCentral
od 2000-12-01
BioMedCentral Open Access
od 2000
Directory of Open Access Journals
od 2000
Free Medical Journals
od 2000
PubMed Central
od 2000
Europe PubMed Central
od 2000
ProQuest Central
od 2009-01-01
Open Access Digital Library
od 2000-01-01
Open Access Digital Library
od 2000-07-01
Open Access Digital Library
od 2000-01-01
Medline Complete (EBSCOhost)
od 2000-01-01
Health & Medicine (ProQuest)
od 2009-01-01
ROAD: Directory of Open Access Scholarly Resources
od 2000
Springer Nature OA/Free Journals
od 2000-12-01
- MeSH
- genové regulační sítě * MeSH
- lidé MeSH
- počítačová grafika * MeSH
- RNA genetika MeSH
- sekvenční analýza RNA metody MeSH
- signální transdukce * MeSH
- software * MeSH
- stanovení celkové genové exprese metody MeSH
- vysoce účinné nukleotidové sekvenování metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
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.
Citace poskytuje Crossref.org
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- $a 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.
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