CITATION.cff

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: DIMet
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: 'Johanna '
    family-names: Galvis Rodriguez
    email: deisy-johanna.galvis-rodriguez@u-bordeaux.fr
    affiliation: CBIB
  - given-names: Joris
    family-names: Guyon
    email: joris.guyon@u-bordeaux.fr
    affiliation: CBIB
  - given-names: Benjamin
    family-names: Dartigues
    email: benjamin.dartigues@u-bordeaux.fr
    affiliation: CBIB
  - given-names: Florian
    family-names: Specque
    email: florian.specque@u-bordeaux.fr
    affiliation: CBIB
  - given-names: Thomas
    family-names: Daubon
    email: thomas.daubon@u-bordeaux.fr
    affiliation: CBIB
  - given-names: Slim
    family-names: Karkar
    email: slim.karkar@u-bordeaux.fr
    affiliation: CBIB
  - given-names: Macha
    family-names: Nikolski
    email: macha.nikolski@u-bordeaux.fr
    affiliation: CBIB
identifiers:
  - type: url
    value: 'https://github.com/cbib/DIMet'
    description: GitHub
repository-code: 'https://github.com/cbib/DIMet'
abstract: >-
  DIMet is a bioinformatics pipeline for differential
  analysis of targeted isotope-labelled data.


  DIMet supports the analysis of full metabolite abundances
  and isotopologue contributions, and allows to perform it
  either in the differential comparison mode or as a
  time-series analysis. As input, the DIMet accepts three
  types of measures: a) isotopologues’ contributions, b)
  fractional contributions (also known as mean enrichment),
  c) full metabolites’ abundances. Specific functions
  process each of the three types of measures separately.


  Note: DIMet is intended for downstream analysis of tracer
  metabolomics data that has been corrected for the presence
  of natural isotopologues. Make sure you that the
  metabolomics platform provides you the output of the
  correction procedure before using this pipeline.
keywords:
  - metabolomics
license: MIT