HiCOPS is a software framework for accelerating database peptide search workflows on supercomputers.HiCOPS provides algorithm-independent parallelizations and optimizations can be extended into new HPC database search algorithms or scalably accelerate the existing ones.
HiCOPS has been implemented using C++17, Python 3.7 and Bash. A high-level graphical abstract of our parallel software framework is shown in the figure.
Learn about our research work in detail in the paper given as follows. You can access the paper via SharedIt. Please cite our paper if you use our work. Thank you.
Muhammad Haseeb, and Fahad Saeed. “High performance computing framework for tera-scale database search of mass spectrometry data.” Nature Computational Science, Volume no. 1, Issue no. 8 (2021): pp no. 550-561. https://doi.org/10.1038/s43588-021-00113-z
Computational Proteomics researchers and developers can integrate their algorithms within the HiCOPS framework. Integration is as simple as implementing conventional (shared-memory) versions of database indexing, filtering, peptide-to-spectrum scoring, post-processing etc. algorithms within HiCOPS.
HiCOPS can seamlessly run on any Linux based workstation, however we recommend running on symmetric multinode (the most common) HPC systems such as the XSEDE Expanse!
HiCOPS is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. Both commercial and academic users can collaborate, contribute, and use the software for research or development by acquiring an appropriate license from: email@example.com.
We welcome contributions via GitHub pull requests. For more information, please refer to Contributing document to learn more or email: firstname.lastname@example.org