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Published on: August 6, 2018
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Preprocessing of raw metabonomic data
1Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Postboks 8905, MTFS, 7489, Trondheim, Norway, muhammad.r.vettukattil@ntnu.no.
Methods in Molecular Biology (Clifton, N.J.)
|February 14, 2015
Summary
Metabolic profiling generates complex data requiring computational preprocessing. This chapter details essential techniques like normalization and peak alignment for accurate analysis of metabolites in biological samples.
Area of Science:
- Metabolomics and Systems Biology
- Analytical Chemistry
- Bioinformatics
Background:
- Metabolic profiling techniques like NMR and MS generate complex data.
- Extracting meaningful biological insights from raw data is challenging due to technical and structural complexity.
Purpose of the Study:
- To cover common data preprocessing techniques in metabonomics.
- To provide an overview of frequently used software tools for data preprocessing.
Main Methods:
- Data preprocessing steps including baseline correction, normalization, and scaling.
- Peak alignment, detection, and quantification methods for spectral data.
- Overview of computational tools for metabonomics data processing.
Main Results:
- Preprocessing transforms complex instrument data into a usable format.
- Standardized preprocessing enhances statistical analysis and biological interpretation.
- Various software tools are available to facilitate these preprocessing steps.
Conclusions:
- Effective data preprocessing is crucial for accurate metabolic profiling.
- Understanding these techniques is essential for researchers in metabonomics.
- The chapter serves as a guide to essential preprocessing steps and tools.
