Skip to main content

MSIGen

MSIGen is designed for converting mass spectrometry imaging (MSI) data from the raw line-scan data to a visualizable format and is designed with nano-DESI MSI in mind. It has premade files for converting to images using a GUI, jupyter notebook, or from the command line.

Installation on Windows

Using Anaconda (https://www.anaconda.com/download), create a new environment titled "MSIGen" with python >=3.9 and <3.12 and activate it. Then, MSIGen can be installed using the pip package manager.

Run the following in Anaconda Prompt one line at a time:

conda create --name MSIGen python=3.11 -y
conda activate MSIGen
pip install MSIGen

For GUI tool:

Download "make GUI shortcut.py" from the other_files folder in the Github repository. Run this code from Anaconda Prompt.

conda activate MSIGen
python "C:/path/to/make GUI shortcut.py"

After running with the actual location of "make GUI shortcut.py", there should be a shortcut called "MSIGen GUI" on your desktop. This runs the GUI for MSIGen.

For Jupyter Notebook Tool:

Download "MSIGen_jupyter.ipynb" from the other_files folder in the Github repository. Open Anaconda Navigator and run Jupyter Notebook in the MSIGen environment. Open "MSIGen_jupyter.ipynb" from Jupyter Notebook.

Alternatively, Jupyter Notebook can be run from Anaconda Prompt. For the first time opening MSIGen:

conda activate MSIGen
pip install notebook
jupyter notebook

After the first run:

conda activate MSIGen
jupyter notebook

For Command Line Interface Tool:

Download "MSIGen_CLI.py" from the other_files folder in the Github repository. Create a configuration file for your experiment. An example can be found in the other_files folder. Run the following in Anaconda Prompt:

conda activate MSIGen
python "C:/Path/to/MSIGen_CLI.py" "C:/path/to/config_file1.json" "C:/path/to/config_file2.json"

Supply one configuration file for each dataset to be processed.

Referencing

If MSIGen was used in your project, please reference it using the following:
[1.] Hernly E, Hu H, Laskin J. MSIGen: An Open-Source Python Package for Processing and Visualizing Mass Spectrometry Imaging Data. J. Am. Soc. Mass Spectrom. 2024, 35, 10, 2315–2323; doi:10.1021/jasms.4c00178

Release files for msigen 0.3.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for msigen 0.3.3
File Size Uploaded
msigen-0.3.3.tar.gz 3.4 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for msigen 0.3.3
File Interpreter ABI Platform
msigen-0.3.3-py3-none-any.whl Python 3 none any Details

Total release size: 6.8 MB

Release files / msigen-0.3.3.tar.gz

Download URL msigen-0.3.3.tar.gz
Size 3.4 MB
Tags Source
SHA-256 checksum
How to use checksums
5ba592706e6736a5b66d58ad870e5feffec73c17a3e57b921ef61f07ca8109a3
BLAKE2b-256 checksum
How to use checksums
3cda3763526435e7c989fef8d9ba2383d2e8989d659562812cc465ba6139d244
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.11.15

Release files / msigen-0.3.3-py3-none-any.whl

Download URL msigen-0.3.3-py3-none-any.whl
Size 3.4 MB
Tags Python 3
SHA-256 checksum
How to use checksums
699a268f0749bbc4953fadab6e1e59dbbf1882cd05cf9f844d00732b73c91c2f
BLAKE2b-256 checksum
How to use checksums
0a61969986f0683cc1e1673806f9c8dea69bdf59bbb100ea03bcbd1e52fd0e83
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.11.15
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page