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inSeqAPI Offline

A Windows desktop application for real-time, adaptive data-dependent acquisition in LC-MS/MS proteomics workflows. inSeqAPI enables dynamic control of Thermo Fisher Orbitrap mass spectrometers by applying configurable filtering strategies and machine learning predictions during acquisition.

Features

  • Define and manage complex acquisition methods with dynamic filtering rules
  • Apply machine learning-based retention time and fragmentation prediction (via ML.NET, ONNX Runtime, and TensorFlow.NET)
  • Configure 30+ filter types for peptide and protein scoring and selection
  • Integrate with external search engines (Comet, Percolator) and data conversion tools (MSConvert)
  • Import and manage protein sequence databases (FASTA format)
  • Visualize data in real time with interactive plotting

The core analysis engine is provided by Scarif, a companion library bundled with the application.

Requirements

  • Windows (x64)
  • .NET Framework 4.6.2
  • Visual Studio 2017 or later (for building from source)
  • Thermo Fisher RawFileReader DLLs (included)

Building

  1. Clone the repository.
  2. Open inSeqAPI_Offline.sln in Visual Studio.
  3. Restore NuGet packages (packages are also cached locally in /packages).
  4. Build the solution in x64 configuration (Debug or Release).

Usage

On first launch, inSeqAPI creates a workspace folder on your Desktop (inSeqAPI/) with subdirectories for methods, databases, modifications, filters, scans, ML models, and plugins.

Use the tabbed interface to:

  1. Methods -- Create or load acquisition method definitions.
  2. Databases -- Import FASTA protein sequence databases.
  3. Filters -- Configure filtering and scoring strategies for peptide selection.
  4. ML Models -- Load retention time and fragmentation predictor models.
  5. Plugins -- Extend functionality with custom analysis plugins.

License

This project is licensed under the MIT License.

Third-party component licenses, including Thermo Fisher RawFileReader, are listed in THIRD_PARTY_NOTICES.txt.

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