Software-assisted reduction of missing values in phosphoproteomics and proteomics isobaric labeling data using MS2 spectrum clustering
Project description
SIMSI-Transfer
Tool for increasing PSM gain from MaxQuant output file.
For testing SIMSI-Transfer after installation, we recommend downloading the TMT11 MS2 raw files from this publication:
Thompson, A., Wölmer, N., Koncarevic, S., Selzer, S. et al., TMTpro: Design, Synthesis, and Initial Evaluation of a Proline-Based Isobaric 16-Plex Tandem Mass Tag Reagent Set. Analytical Chemistry 2019, 91, 15941–15950. doi:10.1021/acs.analchem.9b04474
The MaxQuant and SIMSI-Transfer results of the processed dataset can be downloaded from the following DOIs:
- MaxQuant output (required as input for SIMSI-Transfer): 10.5281/zenodo.6365902
- SIMSI-Transfer output: 10.5281/zenodo.6365638
Running SIMSI-Transfer using the GUI
On Windows, you can download the SIMSI-Transfer_GUI_windows.zip
from the latest release, unzip it and open SIMSI-Transfer.exe
to start the GUI (no installation necessary).
Alternatively, on all platforms, first install SIMSI-Transfer as explained below. Then install PyQt5
(pip install PyQt5
) and run:
python gui.py
Running SIMSI-Transfer from the command line
First install SIMSI-Transfer as explained below, then run SIMSI-Tranfer:
python -m simsi_transfer --mq_txt_folder </path/to/txt/folder> --raw_folder </path/to/raw/folder> --output_folder </path/to/output/folder>
Installation
SIMSI-Tranfer is available on PyPI and can be installed with pip
:
pip install simsi-transfer
Alternatively, you can install directly from this repository:
git clone https://github.com/kusterlab/SIMSI-Transfer.git
pip install .
Building the GUI on Windows
Create a conda environment
Try importing conda_environment.yml
in the Anaconda environment tab.
If that does not work, try the following:
- Set up a new environment, either through the Anaconda UI, or by running the following on the command line:
conda create -n simsi_transfer_gui python=3.8
activate simsi_transfer_gui
- There are some caveats with installing the dependencies. We want to avoid dependence on the MKL (Math Kernel Library) package by numpy/scipy, as this blows up the size of the .exe file over 200MB (see here).
conda install -c conda-forge nomkl numpy pandas pyqt pyinstaller
conda install -c bioconda pyteomics
Building a self-contained executable
Use the build_gui.bat
script to create a self-contained executable.
Reducing size of the executable
Download UPX (https://upx.github.io/) to reduce the DLL file sizes, change the path in build_gui.bat
to point to the UPX folder.
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