To reproduce article data analysis click the button below and run all the cells in opened Google Colab notebook.
CHARDA
CHARDA - Charge Determination Analysis Yaroslav Lyutvinskiy, Amir Ata Saei, Yury Tsybin, Roman Zubarev
Traditionally, mass spectrometry (MS) output is the ion abundance plotted versus ionic mass-to-charge ratio m/z. While employing only commercially available equipment, Charge Determination Analysis (CHARDA) adds a third dimension to MS, estimating for individual peaks their charge states z, starting from z=1, and colour-coding z in m/z spectra. CHARDA combines the analysis of transient decay in Fourier transform (FT) MS with interrogation of mass defects. Being applied to individual isotopic peaks in a complex protein MS/MS dataset, CHARDA facilitates charge state deconvolution of large ionic species in crowded regions, estimating z even in the absence of isotopic distribution (e.g., for monoisotopic mass spectra). CHARDA is fast, robust and consistent with conventional FT MS and FT MS/MS data acquisition procedures. An effective charge resolution Rz≥6 is obtained, with potential for further improvements.
This code is published for article https://chemrxiv.org/engage/chemrxiv/article-details/613a227265db1e3f14b1ab27
"Adding colour to mass spectra: Charge Determination Analysis (CHARDA) assigns charge state to every ion peak"
Currently the article is under review.
Code of CHARDA project is presented in two flawors:
- /CHARDA-pytorch-colab.ipynb - version of CHARDA intended to run in standard colab environment.
- /code/CHARDA.ipynb file - version of CHARDA to run in dedicated docker container
Also /code folder containg binaries of publicly available software hardklor (https://proteome.gs.washington.edu/software/hardklor/) working as deisotoping algoritm for CHARDA.
The notebook /CHARDA-pytorch-colab.ipynb is self-sufficient and takes about 1 hour to complete in standard Google Colab environment with GPU acceleration (as of 4 apr 2023).
Charda can be run both on Linux and windows platforms, however setup for Linux platform is easier to reproduce. Corresponding docker file is located in /environment folder.
Data files for CHARDA were zipped to pass 50Mb limit of github upload. You should unzip them before use.