Skip to content

Progenesis

Introduction

The main documentation for Feature-Based Molecular Networking can be accessed here. See our article.

Below we describe how to use Progenesis QI with the FBMN workflow on GNPS2.

Using Progenesis QI and the Feature-Based Molecular Networking on GNPS2

Progenesis QI is a proprietary LC-MS feature detection and alignment software developed by Nonlinear Dynamics that is compatible with Waters file format and other proprietary and open mass spectrometry format.

Progenesis QI can perform feature detection, alignment and annotation of non-targeted LC-MS/MS data acquired either in data-dependent analysis (DDA) or MSE data independent analysis (DIA), and can also uses the ion mobility spectrometry (IMS) dimension. Feature-based molecular networking (FBMN) can be performed on any of these data types processed with Progenesis QI.

Running Progenesis QI for feature-based molecular networking on GNPS2

For more information on Progenesis QI, please refer to the official documentation at: http://www.nonlinear.com/progenesis/qi/.

1. Import and process the mass spectrometry data with Progenesis QI
  • In Progenesis QI (ver. 2.4, Nonlinear Dynamics), import RAW data from Waters QTof data-independent acquisition (DIA) modes such as SONAR, MSE or HDMSE.
  • Processed data with Progenesis QI and export the results for GNPS2 analysis as indicated below. See the Progenesis QI LC-MS tutorial and the tutorial videos for more informations.
2. Export the processing results

In the menu, under the “Identify Compounds” tab:

  • Select “Export Compound Measurement” to export the feature quantification table (CSV file) containing compound intensity and annotation can be exported (see below).
  • Select “Export fragment database” to the export the MS/MS spectral summary (MSP file) containing the list of representative MS/MS spectra (see below). NOTE: Do not select tags to export

Running a feature-based molecular network on GNPS2

FBMN with Progenesis QI results can be performed using the GNPS2 feature_based_molecular_networking_workflow: please refer to the main FBMN documentation for more information