Research output per year
Research output per year
Abstract
Motivation
Metabolomics is an increasingly common part of health research and there is need for preanalytical data processing. Researchers typically need to characterise the data and to exclude errors within the context of the intended analysis. While some pre-processing steps are common, there is currently a lack of standardization and reporting transparency for these procedures.
Results
Here we introduce metaboprep, a standardised data processing workflow to extract and characterise high quality metabolomics data sets. The package extracts data from pre-formed worksheets, provides summary statistics and enables the user to select samples and metabolites for their analysis based on a set of quality metrics. A report summarising quality metrics and the
influence of available batch variables on the data is generated for the purpose of open disclosure. Where possible, we provide users flexibility in defining their own selection thresholds.
Availability and implementation
metaboprep is an open-source R package available at https://github.com/MRCIEU/metaboprep
Metabolomics is an increasingly common part of health research and there is need for preanalytical data processing. Researchers typically need to characterise the data and to exclude errors within the context of the intended analysis. While some pre-processing steps are common, there is currently a lack of standardization and reporting transparency for these procedures.
Results
Here we introduce metaboprep, a standardised data processing workflow to extract and characterise high quality metabolomics data sets. The package extracts data from pre-formed worksheets, provides summary statistics and enables the user to select samples and metabolites for their analysis based on a set of quality metrics. A report summarising quality metrics and the
influence of available batch variables on the data is generated for the purpose of open disclosure. Where possible, we provide users flexibility in defining their own selection thresholds.
Availability and implementation
metaboprep is an open-source R package available at https://github.com/MRCIEU/metaboprep
| Original language | English |
|---|---|
| Pages (from-to) | 1980-1987 |
| Number of pages | 8 |
| Journal | Bioinformatics |
| Volume | 38 |
| Issue number | 7 |
| Early online date | 4 Feb 2022 |
| DOIs | |
| Publication status | Published - 1 Apr 2022 |
Bibliographical note
Publisher Copyright:© 2022 The Author(s) 2022. Published by Oxford University Press.
Research Groups and Themes
- ALSPAC
Keywords
- Metabolomics
- mass spectrometry
- nuclear magnetic resonance
- evolutionary biology
- epidemiology
- cohort
- pipeline
- ALSPAC
- BiB
Fingerprint
Dive into the research topics of 'metaboprep: an R package for pre-analysis data description and processing'. Together they form a unique fingerprint.Research output
- 9 Citations
- 1 Article (Academic Journal)
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Metabolomics datasets in the Born in Bradford cohort [version 1; peer review: awaiting peer review]
Taylor, K., McBride, N., Goulding, N. J., Burrows, K., Mason, D., Pembrey, L., Yang, T., Azad, R., Wright, J. & Lawlor, D. A., 5 Nov 2020, In: Wellcome Open Research.Research output: Contribution to journal › Article (Academic Journal)
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8074 (C18281/A29019) ICEP2 - Programme Award: Towards improved casual evidence and enhanced prediction of cancer risk and survival
Martin, R. M. (Principal Investigator)
1/10/20 → 30/09/25
Project: Research
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Equipment
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HPC (High Performance Computing) and HTC (High Throughput Computing) Facilities
Alam, S. R. (Manager), Williams, D. A. G. (Manager), Eccleston, P. E. (Manager) & Greene, D. (Manager)
Facility/equipment: Facility