Software Integration for Data Analysis of High-Resolution Liquid Chromatography Tandem Mass Spectra from Low Molecular Weight Organic Matter
EMSL Project ID
50161
Abstract
LC-MS-MS/MS datasets consists of hundreds, thousands and sometimes even hundreds of thousands precursor (MS) and fragmentation spectra (MS/MS). Automation of data analysis is an absolute necessity to ensure completeness and full utilization of acquired spectra. Primary objective of this project is to develop software (Software) for navigation, evaluation and interpretation of high resolution (HR) liquid chromatography (LC) mass spectra (MS) of organic matter (OM) from biotic or abiotic environmental components. Software main feature will be capability of integrating variety of existing tools with single navigation and diagnostics infrastructure allowing unsupervised processing of complete LC tandem MS datasets. Focusing on the low molecular weight compounds, it will serve data analysis needs and increase throughput for metabolomics, proteomics, biofuel and environmental experiments. It will facilitate rapid deployment of existing and evaluation of novel tools where significant challenges in data analysis still exist, namely fragmentation of small NOM molecules or analysis of stable isotopic probing (SIP) samples. We are planning to use existing MS data from variety of EMSL user projects for development and testing. The second objective of this project is to design and compile a reference spectral library (SL) of annotated MS/MS spectra based on large amount of high-resolution spectra acquired in EMSL MS facility. Creating high-quality SL would provide several important benefits: a) cataloged set of reference spectra based on EMSL own instrumentation and data, b) documented training set for machine learning models integrating MS with other analytical platforms (NMR for example) for molecular structure elucidation, and c) making SL publicly available would enhance EMSL capabilities and increase visibility. Proposed Software will provide editing and search functions for SL archiving and access. It will be designed for straightforward deployment in distributed or managed computing environments.
Project Details
Start Date
2018-03-22
End Date
2018-09-30
Status
Closed
Released Data Link
Team
Principal Investigator