title: ToPASeq: an R package for topology-based pathway analysis of microarray and RNA-Seq data.
abstract: 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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Institute of Biostatistics and Analyses, Faculty of Medicine, Masarykova Univerzita, Brno, Czech Republic. ihnatova@iba.muni.cz.
authors.forename: Ivana
authors.initials: I
authors.lastname: Ihnatova
authors.affiliation: Institute of Biostatistics and Analyses, Faculty of Medicine, Masarykova Univerzita, Brno, Czech Republic. budinska@iba.muni.cz.|Central European Institute of Technology, Brno, Czech Republic. budinska@iba.muni.cz.|RECETOX, Faculty of Science, Masarykova Univerzita, Brno, Czech Republic. budinska@iba.muni.cz.
authors.forename: Eva
authors.initials: E
authors.lastname: Budinska
mesh_terms: D003196:Computer Graphics; D020869:Gene Expression Profiling / Q000379:methods*; D053263:Gene Regulatory Networks; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D012313:RNA / Q000235:genetics*; D017423:Sequence Analysis, RNA / Q000379:methods*; D015398:Signal Transduction; D012984:Software
chemical_list: D012313:RNA