• Medientyp: E-Artikel
  • Titel: PAA: an R/bioconductor package for biomarker discovery with protein microarrays
  • Beteiligte: Turewicz, Michael; Ahrens, Maike; May, Caroline; Marcus, Katrin; Eisenacher, Martin
  • Erschienen: Oxford University Press (OUP), 2016
  • Erschienen in: Bioinformatics
  • Sprache: Englisch
  • DOI: 10.1093/bioinformatics/btw037
  • ISSN: 1367-4811; 1367-4803
  • Schlagwörter: Computational Mathematics ; Computational Theory and Mathematics ; Computer Science Applications ; Molecular Biology ; Biochemistry ; Statistics and Probability
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  • Beschreibung: <jats:title>Abstract</jats:title> <jats:p>Summary: The R/Bioconductor package Protein Array Analyzer (PAA) facilitates a flexible analysis of protein microarrays for biomarker discovery (esp., ProtoArrays). It provides a complete data analysis workflow including preprocessing and quality control, uni- and multivariate feature selection as well as several different plots and results tables to outline and evaluate the analysis results. As a main feature, PAA’s multivariate feature selection methods are based on recursive feature elimination (e.g. SVM-recursive feature elimination, SVM-RFE) with stability ensuring strategies such as ensemble feature selection. This enables PAA to detect stable and reliable biomarker candidate panels.</jats:p> <jats:p>Availability and implementation:  PAA is freely available (BSD 3-clause license) from http://www.bioconductor.org/packages/PAA/.</jats:p> <jats:p>Contact:  michael.turewicz@rub.de or martin.eisenacher@rub.de</jats:p>
  • Zugangsstatus: Freier Zugang