# SIMSI-Transfer
[](https://pypi.org/project/simsi_transfer/)
[](https://pypi.org/project/simsi_transfer/)
[](https://pypistats.org/packages/simsi_transfer)
Transferring identifications using MS2 spectrum clustering with MaxQuant search results.
Hamood, F., Bayer, F. P., Wilhelm, M., Kuster, B., & The, M. (2022). _[SIMSI-Transfer: Software-assisted reduction of missing values in phosphoproteomic and proteomic isobaric labeling data using tandem mass spectrum clustering.](https://www.sciencedirect.com/science/article/pii/S1535947622000469)_ Molecular & Cellular Proteomics, 100238.
## Test dataset
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.](https://pubs.acs.org/doi/abs/10.1021/acs.analchem.9b04474)_ Analytical Chemistry 2019, 91, 15941–15950. doi:10.1021/acs.analchem.9b04474
PRIDE link: https://www.ebi.ac.uk/pride/archive/projects/PXD014750
Raw files for TMT-MS2:
- 19070-001.raw
- 19070-002.raw
- 19070-003.raw
- 19070-006.raw
- 19070-007.raw
- 19070-008.raw
The MaxQuant results needed as input to SIMSI-Transfer can be downloaded from Zenodo:
- [10.5281/zenodo.6365902](https://zenodo.org/record/6365902)
For reference, the original SIMSI-Transfer results (v0.1.0) for this dataset can also be downloaded from Zenodo:
- [10.5281/zenodo.6365638](https://zenodo.org/record/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-Transfer:
```shell
python -m simsi_transfer --mq_txt_folder </path/to/txt/folder> --raw_folder </path/to/raw/folder> --output_folder </path/to/output/folder>
```
Alternative command for MS3 acquisition, using the TMT correction factor file exported from MaxQuant:
```shell
python -m simsi_transfer --mq_txt_folder </path/to/txt/folder> --raw_folder </path/to/raw/folder> --output_folder </path/to/output/folder> --tmt_ms_level ms3 --tmt_requantify --tmt_reporter_correction_file </path/to/correction/factor/file.txt>
```
Alternative command using the meta input file for MS3 acquisition, with filtered decoys:
```shell
python -m simsi_transfer --meta_input_file </path/to/meta/file> --output_folder </path/to/output/folder> --tmt_ms_level ms3 --tmt_requantify --filter_decoys
```
A list of all possible arguments is displayed using the help argument:
```shell
python -m simsi_transfer --help
```
## Installation
SIMSI-Transfer is available on PyPI and can be installed with `pip`:
```shell
pip install simsi-transfer
```
Alternatively, you can install SIMSI-Transfer after cloning from this repository:
```shell
git clone https://github.com/kusterlab/SIMSI-Transfer.git
pip install .
```
Raw data
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"description": "# SIMSI-Transfer\n\n[](https://pypi.org/project/simsi_transfer/)\n[](https://pypi.org/project/simsi_transfer/)\n[](https://pypistats.org/packages/simsi_transfer)\n\nTransferring identifications using MS2 spectrum clustering with MaxQuant search results.\n\nHamood, F., Bayer, F. P., Wilhelm, M., Kuster, B., & The, M. (2022). _[SIMSI-Transfer: Software-assisted reduction of missing values in phosphoproteomic and proteomic isobaric labeling data using tandem mass spectrum clustering.](https://www.sciencedirect.com/science/article/pii/S1535947622000469)_ Molecular & Cellular Proteomics, 100238.\n\n## Test dataset\n\nFor testing SIMSI-Transfer after installation, we recommend downloading the TMT11 MS2 raw files from this publication:\nThompson, A., W\u00f6lmer, 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.](https://pubs.acs.org/doi/abs/10.1021/acs.analchem.9b04474)_ Analytical Chemistry 2019, 91, 15941\u201315950. doi:10.1021/acs.analchem.9b04474\n\nPRIDE link: https://www.ebi.ac.uk/pride/archive/projects/PXD014750\n\nRaw files for TMT-MS2:\n- 19070-001.raw\n- 19070-002.raw\n- 19070-003.raw\n- 19070-006.raw\n- 19070-007.raw\n- 19070-008.raw\n\nThe MaxQuant results needed as input to SIMSI-Transfer can be downloaded from Zenodo: \n- [10.5281/zenodo.6365902](https://zenodo.org/record/6365902)\n\nFor reference, the original SIMSI-Transfer results (v0.1.0) for this dataset can also be downloaded from Zenodo:\n- [10.5281/zenodo.6365638](https://zenodo.org/record/6365638)\n\n## Running SIMSI-Transfer using the GUI\n\nOn 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).\n\nAlternatively, on all platforms, first install SIMSI-Transfer as explained below. Then install `PyQt5` (`pip install PyQt5`) and run:\n\n```shell\npython gui.py\n```\n\n## Running SIMSI-Transfer from the command line\n\nFirst install SIMSI-Transfer **as explained below**, then run SIMSI-Transfer:\n\n```shell\npython -m simsi_transfer --mq_txt_folder </path/to/txt/folder> --raw_folder </path/to/raw/folder> --output_folder </path/to/output/folder>\n```\n\nAlternative command for MS3 acquisition, using the TMT correction factor file exported from MaxQuant:\n\n```shell\npython -m simsi_transfer --mq_txt_folder </path/to/txt/folder> --raw_folder </path/to/raw/folder> --output_folder </path/to/output/folder> --tmt_ms_level ms3 --tmt_requantify --tmt_reporter_correction_file </path/to/correction/factor/file.txt>\n```\n\nAlternative command using the meta input file for MS3 acquisition, with filtered decoys:\n\n```shell\npython -m simsi_transfer --meta_input_file </path/to/meta/file> --output_folder </path/to/output/folder> --tmt_ms_level ms3 --tmt_requantify --filter_decoys\n```\n\nA list of all possible arguments is displayed using the help argument:\n```shell\npython -m simsi_transfer --help\n```\n\n## Installation\n\nSIMSI-Transfer is available on PyPI and can be installed with `pip`:\n\n```shell\npip install simsi-transfer\n```\n\nAlternatively, you can install SIMSI-Transfer after cloning from this repository:\n\n```shell\ngit clone https://github.com/kusterlab/SIMSI-Transfer.git\npip install .\n```\n\n",
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