Abstract:
Metabolomics, defined as the study of an organism’s entire metabolic profile,
is a direct read-out of the physiological changes at the cellular level and has
the potential to positively inform drug-target discovery and biomarker
identification.
Mass Spectrometry is one of the most popular techniques used to measure the
levels of metabolites present in biological samples. Tandem Mass
Spectrometry, and more commonly, Data Dependent Acquisition (DDA) has
become a trusted technique for metabolite identification and quantification
due to its dependence on spectral pattern matching with existing libraries.
Since existing mass spectrometry data processing tools are either
vendor-specific or difficult to use, the DDA workflow has been added to
El-MAVEN, an open-source mass spectrometry data processing tool,
maintained by Elucidata. Spectral matching capabilities have been added as
part of the targeted DDA workflow and algorithmic improvements have been
made to the untargeted workflow for optimum results.
Additional widgets and features have been added for a better user experience in
data curation. The improvements have been validated against known
standards using datasets obtained from Elucidata’s partner labs.
