Isotopologue and mass spectrum calculator
all dependencies are available via pip
- numpy
- pandas
- scipy
- IsoSpecPy
- gooey
pip wheel TBD
conda TBD
For the time being Linux users need to clone the rep and install dependencies manually.
Windows users can either clone the repository or use a Release which comes bundled with Winpython
containing all necessary packages. Unzip and launch via isotool_win.bat.
IsoTool comes with a .csv-file containing the terrestrial abundances of known elements
(data/isotopes_terrestrial.csv), retrieved from the National Institute of Standards
and Technology.
It is possible to define custom isotopes, e.g. for isotopoic labeling experiments. The definitions have to be stored in a csv-file similar to the terrestrial isotope definitions.
element_symbol,mass_number,atomic_mass,abundance,
C,12,12.0000000000000,0.01
C,13,13.0033548350723,0.99
X,..,................,....These files can easily be edited in any spreadsheet or text editor.
The Molecule file contains the elemental composition of the chemical species of interest in its neutral state.
element,n
C,54
X,20
..,..
Elements appearing in the molecule file need to have their isotopes defined in the Isotope file used for the calculations.
Default parameters are taken from Ref. 1.
All outputs are in csv format, that can be edited in any spreadsheet or text editor.
The centroids.csv file contains a table with m/z, p and the exact isotopic composition of each
of the calculated isotopologue.
The spectrum.csv file contains the profile spectrum of the given chemical species after modeling
and summing Gaussian peaks for the calculated isotopolgues.
The exact methodology and an example application are described in [1] . The underlying algorithm for the fast calculation of isotopologue probabilities (IsoSpec) has been described by Łącki et al.[2], while the workflow for Gaussian peak simulation has been heavily inspired by functionality available in mineXpert [3].
IsoTool is written in Python 3 and makes use of the numpy [4], pandas[5] and scipy[6] libraries as well as the Python bindings for IsoSpec[2]. The GUI was created using the gooey package [7].
[1] Atze, H.; Rusconi, F.; Arthur, M. Heavy Isotope Labeling and Mass Spectrometry Reveal Unexpected Remodeling of Bacterial Cell Wall Expansion in Response to Drugs. bioRxiv 2021. https://doi.org/10.1101/2021.08.06.454924.
[2] IsoSpec: Hyperfast Fine Structure Calculator Mateusz K. Łącki, Michał Startek, Dirk Valkenborg, and Anna Gambin Analytical Chemistry 2017 89 (6), 3272-3277 DOI: 10.1021/acs.analchem.6b01459
[3] mineXpert: Biological Mass Spectrometry Data Visualization and Mining with Full JavaScript Ability, Filippo Rusconi, Journal of Proteome Research 2019 18 (5), 2254-2259, DOI: 10.1021/acs.jproteome.9b00099
[4] Stéfan van der Walt, S. Chris Colbert and Gaël Varoquaux. The NumPy Array: A Structure for Efficient Numerical Computation, Computing in Science & Engineering, 13, 22-30 (2011), DOI:10.1109/MCSE.2011.37
[5] Wes McKinney. Data Structures for Statistical Computing in Python, Proceedings of the 9th Python in Science Conference, 51-56 (2010)
[6] Virtanen, P., Gommers, R., Oliphant, T.E. et al. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nat Methods 17, 261–272 (2020). https://doi.org/10.1038/s41592-019-0686-2