title: mAPKL: R/ Bioconductor package for detecting gene exemplars and revealing their characteristics.
abstract: BACKGROUND
  So far many algorithms have been proposed towards the detection of significant genes in microarray analysis problems. Several of those approaches are freely available as R-packages though their engagement in gene expression analysis by non-bioinformaticians is usually a frustrating task. Besides, only some of those packages offer a complete suite of tools starting from initial data import and ending to analysis report. Here we present an R/Bioconductor package that implements a hybrid gene selection method along with a bunch of functions to facilitate a thorough and convenient gene expression profiling analysis.
  
  
  RESULTS
  mAPKL is an open-source R/Bioconductor package that implements the mAP-KL hybrid gene selection method. The advantage of this method is that selects a small number of gene exemplars while achieving comparable classification results to other well established algorithms on a variety of datasets and dataset sizes. The mAPKL package is accompanied with extra functionalities including (i) solid data import; (ii) data sampling following a user-defined proportion; (iii) preprocessing through several normalization and transformation alternatives; (iv) classification with the aid of SVM and performance evaluation; (v) network analysis of the significant genes (exemplars), including degree of centrality, closeness, betweeness, clustering coefficient as well as the construction of an edge list table; (vi) gene annotation analysis, (vii) pathway analysis and (viii) auto-generated analysis reporting.
  
  
  CONCLUSIONS
  Users are able to run a thorough gene expression analysis in a timely manner starting from raw data and concluding to network characteristics of the selected gene exemplars. Detailed instructions and example data are provided in the R package, which is freely available at Bioconductor under the GPL-2 or later license http://www.bioconductor.org/packages/3.1/bioc/html/mAPKL.html.
authors.affiliation: Center of Systems Biology, Biomedical Research Foundation of the Academy of Athens, 4 Soranou Ephessiou Street, Athens, 115 27, Greece. argisake@gmail.gr.|Department of Informatics and Telecommunications, National & Kapodistrian University of Athens, Athens, Greece. argisake@gmail.gr.
authors.forename: Argiris
authors.initials: A
authors.lastname: Sakellariou
authors.affiliation: Center of Systems Biology, Biomedical Research Foundation of the Academy of Athens, 4 Soranou Ephessiou Street, Athens, 115 27, Greece. gspyrou@bioacademy.gr.
authors.forename: George
authors.initials: G
authors.lastname: Spyrou
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D020869:Gene Expression Profiling / Q000379:methods*; D053263:Gene Regulatory Networks; D006801:Humans; D058977:Molecular Sequence Annotation; D012984:Software