IsoPat 3.0

Isotope Pattern Deconvolution for Mass Spectrometry

Determine the relative amounts of non-labeled (d₀) and isotope-labeled species (d₁, d₂, ..., d_n) in a mixture from mass spectrometry data using least-squares optimization.

Input Data

Unlabeled Pattern [a.u.] Natural isotope distribution (abundance): M, M+1, M+2, ...

Analyte Pattern [a.u.] Measured pattern of the labeled mixture (abundance)

Max. Labels (n) Maximum number of isotope labels

Mass Shift Mass difference per label

Results

Enter data and click "Calculate" to see results.

About

IsoPat uses least-squares optimization to deconvolve mass spectrometric patterns of mixtures of labeled compounds. The algorithm determines the relative amounts of each (un)labeled species (d₀ = unlabeled, d₁ = one label, etc.) based on the mass pattern of the unlabeled compound and the information of the maximum number of labels and the mass difference between label and non-label (e.g. 1 for H/D or 2 for H/T).

Reference: Gruber et al. (2007) J. Org. Chem. 72, 5778-5783

The Excel file mentioned in the publication from 2007 (IsoPat2) can be downloaded here.

Installation: pip install isopat

Source Code: GitHub | PyPI