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.

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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

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article

Data curation of extracellular enzyme activity spectrophotometric or fluorometric data

Paul Iturbe-Espinoza, Rumakanta Sapkota, Anne Winding, Nicole Christiansen
3 citations
MethodsX
Metabolomics and Mass Spectrometry Studies
2.42
article

Data curation of extracellular enzyme activity spectrophotometric or fluorometric data

Paul Iturbe-Espinoza, Rumakanta Sapkota, Anne Winding, Nicole Christiansen
article en
3 citations

Abstract

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.

MethodsXVol. 14
Copenhagen Business School (DK), Aarhus University (DK)
Ministeriet for Fø devarer, Landbrug og Fiskeri, European Commission, Ministry of Environment, Energistyrelsen, Grønt Udviklings- og Demonstrations Program
Zero hunger
Openalex Percentile: Top 12%
Metabolomics and Mass Spectrometry Studies
2.42
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Data curation of extracellular enzyme activity spectrophotometric or fluorometric data — Paul Iturbe-Espinoza, Rumakanta Sapkota, et al. · MethodsX (2025) | TGRS Research Map | TGRS