notame is an R-based tool developed at the University of Eastern Finland and Afekta Technologies by our group (Klåvus et al.) for nontargeted metabolomics data processing. It features a streamlined workflow consisting of reading in exported data from signal detection software (currently MS-DIAL), correcting signal intensity drift, identifying and flagging low-quality molecular features, imputing missing values, correcting batch effects, clustering similar molecular features, and providing a variety of useful statistical and data visualization features. We currently use this tool in all our metabolomics projects involving medium to large sample sets.
Here's the GitHub link to the script and example data presented at the workshop as well as the workshop slides.
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