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Interactive GUI

MS-MINT includes a Solara-based graphical interface for interactive analysis in Jupyter notebooks.

Installation

Install with GUI support:

pip install ms-mint[gui]

Usage

In Jupyter Notebook

from ms_mint.gui import MintGui

MintGui()

Standalone Application

solara run ms_mint.gui.app:MintGui

Interface Overview

The GUI is organized into five tabs:

MS Files Tab

  • File Selection: Load MS files using glob patterns (e.g., ./data/*.mzML)
  • Metadata Panel: View and edit sample metadata
  • Supports mzML, mzXML, mzMLb, and parquet formats

Targets Tab

  • Target Loading: Upload target lists (CSV/Excel)
  • Target Management: Reorder, activate/deactivate targets
  • RT Optimization: Automatically optimize retention time windows based on actual chromatographic data

Processing Tab

  • Run Analysis: Process MS files with loaded targets
  • Progress Tracking: Monitor processing status
  • Export Results: Save results to CSV
  • Settings:
    • Processing mode (standard/parallel)
    • RT margin adjustment
    • Thread count for parallel processing

Results Tab

  • Results Table: View peak integration results
  • Crosstab View: Pivot table of peak areas by sample and metabolite

Visualization Tab

  • Heatmaps: Hierarchical clustering visualization
  • Peak Shapes: Chromatographic peak profiles
  • 2D Histograms: Raw data exploration
  • Export plots in multiple formats (PNG, PDF, SVG)

The sidebar provides global settings:

Setting Description
Working Directory Base path for file operations
RT Unit Display retention times in seconds or minutes
Image Format Export format for plots
Threads Number of parallel processing threads
Session Save/load analysis state

Workflow Example

  1. Load MS Files: Navigate to MS Files tab, enter glob pattern, click Load
  2. Load Targets: Switch to Targets tab, upload target list CSV
  3. Optimize RT (optional): Click "Optimize RT" to refine retention time windows
  4. Run Processing: Go to Processing tab, click Run
  5. View Results: Check Results tab for peak areas
  6. Visualize: Use Visualization tab for heatmaps and peak shapes
  7. Export: Save results and session for later use

Session Management

Save your analysis state:

  • Save Session: Preserves loaded files, targets, results, and settings
  • Load Session: Restore a previous analysis state

Sessions are saved to the working directory as mint_session.pkl.

See Also