Journal
BIOINFORMATICS
Volume -, Issue -, Pages -Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btac647
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Funding
- University of Vienna
- Austrian Science Fund [SFB-Fusarium-37 (-11, -15)]
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This article presents a method for targeted and untargeted detection of homologue series using an R package, homologueDiscoverer, and provides evaluation and management through interactive plots and simple local database functionalities.
Untargeted metabolomics data analysis is highly labour intensive and can be severely frustrated by both experimental noise and redundant features. Homologous polymer series is a particular case of features that can either represent large numbers of noise features or alternatively represent features of interest with large peak redundancy. Here, we present homologueDiscoverer, an R package that allows for the targeted and untargeted detection of homologue series as well as their evaluation and management using interactive plots and simple local database functionalities.
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