Data curation of extracellular enzyme activity spectrophotometric or fluorometric data
Extracellular Enzyme Activity (EEA) assay is an important tool in soil ecology. During data analyses, we experienced outlier time-point measurements and samples deviating from a linear development. However, we lacked a satisfying method for curating these data, and our goal is to provide a standardized and transparent method for data curation of EEA data. This was done in the form of an R function that allows for both customized and standardized approaches to data curation of EEA data. When testing the function on multiple datasets, we found that our data curation did change EEA levels, but only in instances close to minimum detection levels. During curation, R² generally increased, resulting in more samples with acceptable R² values. The function provides a relatively unbiased, easy-to-use method for EEA data curation that will hopefully improve the transparency and standardization of EEA data curation. Main outcomes:•Function for curation of Extracellular Enzyme Activity data.•Improving transparency and standardization.•Relatively unbiased, easy-to-use method.
Authors
- Paul Iturbe-Espinoza (ORCID: https://orcid.org/0000-0002-1313-5532)
- Rumakanta Sapkota (ORCID: https://orcid.org/0000-0003-4735-1046)
- Anne Winding (ORCID: https://orcid.org/0000-0002-7491-4548)
- Nicole Christiansen
Institutions
- Copenhagen Business School (DK)
- Aarhus University (DK)
Publication Details
- Journal
- MethodsX
- Published
- 2025-04-23
- DOI
- https://doi.org/10.1016/j.mex.2025.103328
- Citations
- 3
- Primary Topic
- Metabolomics and Mass Spectrometry Studies
- Type
- article
- Field-Weighted Citation Impact
- 2.42
Funders
- Ministeriet for Fø devarer, Landbrug og Fiskeri
- European Commission
- Ministry of Environment
- Energistyrelsen
- Grønt Udviklings- og Demonstrations Program