Skip to content

Promote peptide identification using accurate and comprehensive precursors. https://doi.org/10.1021/acs.jproteome.3c00293

Notifications You must be signed in to change notification settings

ctarn/PepPre.jl

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

PepPre.jl

PepPre is a method to detect peptide precursors from LC-MS map to promote peptide identification, validation, etc.

For User

Please visit https://peppre.ctarn.io for access to software or documents.

Please contact [email protected] if you have any problems.

For Developer

Install Julia

Please install Julia (version 1.9 or newer) from https://julialang.org.

Clone the Repos

Please clone MesMS.jl and PepPre.jl by:

git clone [email protected]:MesMS/MesMS.jl.git
git clone [email protected]:ctarn/PepPre.jl.git

Compile the Project

Please cd to the root folder of PepPre.jl:

cd PepPre.jl

And the compile the project using:

julia --project=. util/complie.jl

The complied files would be located at ./tmp/{your platform}/.

Build GUI and Installer

Finally, please run the scripts based on your platform if you want to build the graphic user inerface and package the software:

sh util/build_linux.sh
# or 
sh util/build_macos.sh
# or
./util/build_windows.bat

Python, PyInstaller, and Tkinter are required to build the GUI. You can also call PepPre or PepPreView from command line directly using the compiled files.

The packaged software would be located at ./tmp/release/.

Citation

BibTeX

@article{Tarn2024PepPre,
    author = {Ching Tarn and Yu-Zhuo Wu and Kai-Fei Wang},
    title = {PepPre: Promote Peptide Identification Using Accurate and Comprehensive Precursors},
    journal = {Journal of Proteome Research},
    doi = {10.1021/acs.jproteome.3c00293},
    url = {https://doi.org/10.1021/acs.jproteome.3c00293},
    year = {2024},
    type = {Journal Article}
}

APA

Tarn, C., Wu, Y.-Z., & Wang, K.-F. (2024). PepPre: Promote Peptide Identification Using Accurate and Comprehensive Precursors. Journal of Proteome Research. https://doi.org/10.1021/acs.jproteome.3c00293