Fig. 1: The concept of ion identity molecular networking (IIMN).
From: Ion identity molecular networking for mass spectrometry-based metabolomics in the GNPS environment
The workflow integrates a MS1 feature grouping to connect different ion species of the same compound and b feature-based molecular networking to connect similar compound structures based on MS2 spectral similarity to yield c combined networks. d highlights the data processing steps to create IIMN networks in MZmine and GNPS. After feature detection and alignment across multiple samples, features are grouped based on the correlation of their chromatographic feature shapes (intensity profiles) and other MS1 characteristics. Subsequently, ion species of grouped features are identified with an ion identity library generated based on user input for included adducts, in-source modifications, and a maximum multimer parameter. After uploading these results to the GNPS web server, the IIMN workflow generates combined networks and an alternative output with all IIN collapsed into single molecular nodes to reduce complexity and redundancy.
