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MsReport documentation

MsReport is a Python library for post-processing quantitative proteomics data from bottom-up mass spectrometry.

Project documentation status

Currently, only the API documentation and installation instructions are available. The rest of the documentation is a work in progress and may take some time to complete. Please refer to the API reference for detailed information about MsReport's modules, classes and functions.

Installation

If you do not already have a Python installation, we recommend installing the Anaconda distribution or Miniconda distribution from Continuum Analytics, which already contains a large number of popular Python packages for Data Science. Alternatively, you can also get Python from the Python homepage. Note that MsReport requires Python version 3.10 or higher.

The following command will install MsReport and its dependencies by using a wheel file.

pip install msreport

To uninstall the MsReport library use:

pip uninstall msreport

Installation when using Anaconda

To install the MsReport library using Anaconda, you need to either activate a custom conda environment or install it into the default base environment. Open the Anaconda Navigator, activate the desired conda environment or use the base environment, and then open a command line by running the "CMD.exe" application. Finally, use the pip install command as before.

Optional Dependencies

R Integration

MsReport provides an interface to the R package LIMMA for differential expression analysis. To use this functionality, you need:

  • A local installation of R (version 4.0 or higher).
  • The system environment variable R_HOME set to the R home directory.
  • To install msreport with the optional dependencies for R integration.
pip install msreport[R]

Setting the R_HOME environment variable

On Windows, you may need to restart your computer after modifying the system environment variables for the changes to take effect. To find the R home directory, you can run the following command in R:

normalizePath(R.home("home"))

For example, the R home directory might look like this on Windows: C:\Program Files\R\R-4.2.1