LAUSR

Gas chromatography and liquid chromatography coupled to mass spectrometry are used extensively in untargeted metabolomics, which involves the profiling of small metabolites in biological samples. The complex raw dataset produced from untargeted metabolomics requires proper processing before it can be statistically analyzed and interpreted. This chapter describes a high-throughput data processing workflow routinely used in our laboratory, including feature detection and alignment, data reduction, and spectral-matching-based annotation. This semiautomated workflow uses vendor neutral data file formats and freely available data processing tools and therefore can be readily implemented on datasets acquired from instruments of different vendors.