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MarVis-Filter:质谱数据的排名、过滤、加合物和同位素校正

MarVis-Filter: ranking, filtering, adduct and isotope correction of mass spectrometry data.

作者信息

Kaever Alexander, Landesfeind Manuel, Possienke Mareike, Feussner Kirstin, Feussner Ivo, Meinicke Peter

机构信息

Department of Bioinformatics, Institute of Microbiology and Genetics, Georg-August-University Göttingen, 37077 Göttingen, Germany.

出版信息

J Biomed Biotechnol. 2012;2012:263910. doi: 10.1155/2012/263910. Epub 2012 Apr 5.

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.

摘要

统计排名、过滤、加合物检测、同位素校正和分子式计算是代谢组学研究中处理质谱数据的关键任务。为了获得高质量的数据集,需要一个整合所有这些方法的框架。我们展示了MarVis-Filter软件,它为处理质谱数据提供了成熟且专门的方法。对于多变量强度谱的排名和过滤任务,MarVis-Filter提供了方差分析和Kruskal-Wallis检验,并对多重假设检验进行了调整。加合物和同位素校正基于一种新颖的算法,该算法考虑了强度谱的相似性,并允许用户定义电离规则。分子式计算利用了加合物和同位素校正的结果。为了进行全面分析,MarVis-Filter提供了一个交互式界面,用于合并来自正离子和负离子模式的数据集。该软件在一个代谢案例研究中得到了示例性应用,在该研究中,十八烷类化合物可被识别为植物受伤的标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85cf/3328170/79a1f215549c/JBB2012-263910.001.jpg

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