This implementation detects potential bromide & chloride isotopes by analysing the differences between data point mass to charge ratios and intensities, accounting for margin of error. Detection can be filtered by a configurable minimum intensity value.
Data is input/output through CSV files. It is expected that the provided input data is sorted by ascending 'm/z'
ratios. config.py provides configurable options for the detection process.
Both bromine and chlorine have two stable isotopes, each isotope with a relative abundance. When comparing the data points, we are looking for 'm/z' deltas and intensity ratios matching the characteristics of these isotopes. A 'match' between two data points indicates a potential pair of stable isotopes type one and type two, which then may be investigated further.
Where possible, data will be split into chunks to be multi-processed (depending on if suitable boundaries can be found). It runs in O(n^2) time. Practically, worst case performance will be when the minimum intensity value is very low, where 'm/z' distances likely to be less sparse and it is more difficult to chunk the data. Binary searching is also relied upon for efficient iteration.
python@3.10pyarrow@11.0.0