LC-MS trend detection with the new enviMass workflow interface

enviMass is a data-mining workflow for the automatized trend detection in liquid chromatography (LC) mass spectrometry (MS) measurement sequences, including a bundle of additional functionalities such as targeted screening, nontargeted grouping, homologue series detection or quantification. It is freely available for private usage, universities and contributors. Please note that enviMass is mainly developed for 64bit Windows for the time being.

Isotopologue tree The enviMass workflow features:

  • File upload (.mzXML format; direct conversion and upload of Thermo .raw files via ProteoWizard supported); batch file upload from folder.

  • Auto-parametrized noise removal.

  • Chomatogram extraction (EICs, XICs), peak picking and interactive data visualization.

  • Upload of suspect, target and internal standard compounds and resolution-specific calculation of their isotopic patterns.

  • Mass recalibration.

  • Intensity normalization; based on median intensities or internal standard compounds.

  • Replicate intersection filter.

  • Compound screening; includes filewise interpolation of limits of detection (LODs) and a combinatorial algorithm to find the most plausible matches of compound isotopic patterns.

  • Blind and blank file subtraction steps.

  • Quality control steps.

  • Isotopologue (Sciex TOF and Thermo Orbitrap instruments) and adduct grouping, componentization.

  • EIC correlation.

  • Homologue series detection.

  • Estimation of atom counts for nontarget components.

  • Extraction of time-intensity profiles.

  • Profile trend detection; works for hundreds of uploaded files and several thousand profiles.

  • Calibration, quantification and recovery with internal standards.

  • Adapative workflow structure - changes in parameters, compounds, files or workflow choices are traced and calculations adapted accordingly to minimize runtime.

  • User-friendly and interactive interface and project structure.

  • Workflow data availability in the R statistical environment - countless possibilities for custom-tailored analysis such as large-scale clustering, PCA or simple Venn-diagrams.

  • Handles positive and negative ionization modes in one project.