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MarVis-Filter: ranking, filtering, adduct and isotope correction of mass spectrometry data.
Kaever, Alexander; Landesfeind, Manuel; Possienke, Mareike; Feussner, Kirstin; Feussner, Ivo; Meinicke, Peter.
Afiliação
  • Kaever A; Department of Bioinformatics, Institute of Microbiology and Genetics, Georg-August-University Göttingen, 37077 Göttingen, Germany. alex@gobics.de
J Biomed Biotechnol ; 2012: 263910, 2012.
Article em En | MEDLINE | ID: mdl-22550397
ABSTRACT
Statistical ranking, filtering, adduct detection, isotope correction, and molecular formula calculation are essential tasks in processing mass spectrometry data in metabolomics studies. In order to obtain high-quality data sets, a framework which incorporates all these methods is required. We present the MarVis-Filter software, which provides well-established and specialized methods for processing mass spectrometry data. For the task of ranking and filtering multivariate intensity profiles, MarVis-Filter provides the ANOVA and Kruskal-Wallis tests with adjustment for multiple hypothesis testing. Adduct and isotope correction are based on a novel algorithm which takes the similarity of intensity profiles into account and allows user-defined ionization rules. The molecular formula calculation utilizes the results of the adduct and isotope correction. For a comprehensive analysis, MarVis-Filter provides an interactive interface to combine data sets deriving from positive and negative ionization mode. The software is exemplarily applied in a metabolic case study, where octadecanoids could be identified as markers for wounding in plants.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Espectrometria de Massas / Algoritmos / Software / Biologia Computacional / Metabolômica Idioma: En Ano de publicação: 2012 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Espectrometria de Massas / Algoritmos / Software / Biologia Computacional / Metabolômica Idioma: En Ano de publicação: 2012 Tipo de documento: Article País de afiliação: Alemanha