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General Reactomics Data Analysis Framework for Retrieving Chemical Relationship
Monday, March 08, 2021: 10:05 AM - 10:25 AM
Speaker(s)
Description
In order to interpret statistical findings, Mass spectrometry-based untargeted metabolomics studies prioritize the arduous task of identification of small molecule features. However, we show that data mining mass-spectrometry data using paired mass distances reveals general chemical relationships without annotation of unknown ions. Further, this approach, called pmd-based reactomics, can be used for both qualitative and quantitative analysis of untargeted mass-spectrometry data. Our pmd-based reactomics data analysis framework includes removal of redundant peaks, determination of high frequency paired mass distances, and network analysis for both paired mass distances and peak intensities. The topological properties of the network analysis such as average distances of network clusters and negative correlation edges between two clusters can facilitate interpretation of biological functions or suggest whether untargeted features are potentially endogenous or exogenous. Discovery of changes in pmd-based reactomics’ networks between sample groups may reflect changes in reactive feature pairs linked with general chemical relationships which can be targeted in future studies. This framework and applications are demonstrated using publically available data, and are freely available for download (https://yufree.github.io/pmd/).
Additional Info
Keywords: Please select up to 4 keywords ONLY:
Bioinformatics,Data Analysis and Manipulation,Genomics, Proteomcs and Other 'Omics',New Method
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