Metadata-Version: 2.4
Name: sita-core
Version: 0.1.0
Summary: Natural-abundance correction for GC-MS mass distribution vectors from 13C stable-isotope tracer experiments
Project-URL: Homepage, https://github.com/CMonnin/SITA
Project-URL: Source, https://github.com/CMonnin/SITA
Project-URL: Issues, https://github.com/CMonnin/SITA/issues
Author-email: Cian Monnin <cianmonnin@gmail.com>
License-Expression: MIT
Keywords: 13C,GC-MS,flux-analysis,isotope,mass-spectrometry,metabolomics
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Chemistry
Requires-Python: >=3.10
Requires-Dist: numpy>=1.26
Description-Content-Type: text/markdown

# 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

```python
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](https://github.com/CMonnin/SITA) for the full
documentation, CLI, and Flask UI.
