mzExtract

mzExtract extracts and integrates features from high-resolution liquid chromatography-mass spectrometry (LC-MS) data to enable untargeted metabolomics profiling and cross-sample feature matching.

Key Features:

• Automated Feature Extraction: Automates extraction and integration of features from high-resolution LC-MS datasets.
• Grouped Feature-Sets: Clusters individual features into compound-related grouped feature-sets that facilitate interpretation, identification, and matching across samples.
• Scalability and Versatility: Operates on a per-sample and per-mass trace basis and applies to lipidomics as well as time-of-flight (TOF) MS, capillary electrophoresis (CE)-MS, gas chromatography-MS (GC-MS), and multiple reaction monitoring (MRM) data.
• Comparative Performance: Matches integration results for known target metabolites produced by vendor software while extracting at least ten times more feature-sets.

Scientific Applications:

• Untargeted metabolic profiling: Enables comprehensive exploratory profiling for discovery of novel metabolites and metabolic signatures in life-science studies using high-resolution LC-MS.
• Lipidomics and cross-platform MS analyses: Supports lipidomics studies and broader applications across TOF, CE-MS, GC-MS, and MRM workflows for comparative and large-scale analyses.

Methodology:

Processes high-resolution LC-MS data by extracting and integrating individual features into grouped feature-sets on a per-sample and per-mass trace basis; the process is automated and has been demonstrated using data from 128 lipidomics samples.