Metadata-Version: 2.1
Name: simsi-transfer
Version: 0.2.2
Summary: Software-assisted reduction of missing values in phosphoproteomics and proteomics isobaric labeling data using MS2 spectrum clustering
Home-page: https://github.com/kusterlab/SIMSI-Transfer
License: Apache-2.0
Keywords: mass spectrometry,missing values,clustering,proteomics,quantification
Author: Firas Hamood
Author-email: firas.hamood@tum.de
Requires-Python: >=3.8,<4.0
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Dist: lxml (>=4.8.0,<5.0.0)
Requires-Dist: numpy (>=1.18.1,<2.0.0)
Requires-Dist: pandas (>=1.3.0,<2.0.0)
Requires-Dist: pyteomics (>=4.5.3,<5.0.0)
Project-URL: Repository, https://github.com/kusterlab/SIMSI-Transfer
Description-Content-Type: text/markdown

# 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:

```shell
python gui.py
```

## Running SIMSI-Transfer from the command line

First install SIMSI-Transfer as explained below, then run SIMSI-Tranfer:

```shell
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`:

```shell
pip install simsi-transfer
```

Alternatively, you can install directly from this repository:

```shell
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:

1. 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
```

2. 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](https://github.com/pyinstaller/pyinstaller/issues/2270)).

```
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**.

