Influence of the extraction protocol on the chemical diversity of tree woody-tissue metabolome

  1. Vinchira-Villarraga, Diana 1
  2. Milenkovic, Vanja 1
  3. Wei, Jiaqi 1
  4. Grace, Emily R 1
  5. Hinton, Katherine G 1
  6. Webster, Amy J 1
  7. Dhaouadi, Sabrine 1
  8. Forero, Abel M 2
  9. Castellanos, Leonardo 3
  10. Ramos, Freddy A 3
  11. Harrison, Richard J 4
  12. Rabiey, Mojgan 5
  13. Jackson, Robert W 1
  1. 1 University of Birmingham
    info

    University of Birmingham

    Birmingham, Reino Unido

    ROR https://ror.org/03angcq70

  2. 2 Universidade da Coruña
    info

    Universidade da Coruña

    La Coruña, España

    ROR https://ror.org/01qckj285

  3. 3 Universidad Nacional de Colombia
    info

    Universidad Nacional de Colombia

    Bogotá, Colombia

    ROR https://ror.org/059yx9a68

  4. 4 Wageningen University & Research
  5. 5 University of Warwick
    info

    University of Warwick

    Coventry, Reino Unido

    ROR https://ror.org/01a77tt86

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Editor: Zenodo

Ano de publicación: 2023

Tipo: Dataset

CC BY 4.0

DOI: 10.5281/ZENODO.8351669 lock_openAcceso aberto editor

Resumo

Scripts and dataset for Vinchira-Villarraga et al., 2023 "Influence of the extraction protocol on the chemical diversity of tree woody-tissue metabolome". The files label as A1, C6, H2/HCN2 and O1 correspond to the dataset obtained for Ash, Cherry, Horse-chestnut and Oak respectively. _batch.xml files contains the script for the pre-processing of .mzML mass spectrometry data created on MzMine 3.2.8. The file can be uploaded to newer versions of MzMine, but due to the addition of new modules, some parameters name have changed. _SIRIUS.mfg files contains the mass spectrometry data of each dataset for analysis in SIRIUS. The files were used for chemical formula prediction, classification and compound annotation using SIRIUS 4.0 _quant.csv correspond to the output matrix as it was obtained from MzMine without noise, adducts and highly variable features filtering. _abundance.csv correspond to the output matrix after noise, adducts and highly variable features filtering.