Natural-abundance correction for GC-MS mass distribution vectors from 13C stable-isotope tracer experiments
Project description
sita-core
Natural-abundance correction for GC-MS mass distribution vectors from 13C stable-isotope tracer experiments.
Pure-Python library implementing the corrections described in Nanchen, Fuhrer & Sauer (2007) Determination of Metabolic Flux Ratios From 13C-Experiments and Gas Chromatography–Mass Spectrometry Data, Methods in Molecular Biology 358.
Install
pip install sita-core
Usage
from sita_core import LabelledCompound
ala = LabelledCompound(
formula="C11H26NO2Si2",
labelled_element="C",
backbone_c=3,
mdv_a=[0.6228, 0.1517, 0.0749, 0.1507],
)
corr = ala.correction_matrix()
mdv_star = ala.mdv_star()
See the project repository for the full documentation, CLI, and Flask UI.
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