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Updated: Feb 10, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
Guidelines for Sample Normalization to Minimize Batch Variation for Large-Scale Metabolic Profiling of Plant Natural
Saleh Alseekh1,2, Si Wu3,4, Yariv Brotman3,4
1Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany. alseekh@mpimp-golm.mpg.de.
Abstract:
Recent methodological advances in both liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) have facilitated the profiling highly complex mixtures of primary and secondary metabolites in order to investigate a diverse range of biological questions. These techniques usually face a large number of potential sources of technical and biological variation. In this chapter we describe guidelines and normalization procedures to reduce the analytical variation, which are essential for the high-throughput evaluation of metabolic variance used in broad genetic populations which commonly entail the evaluation of hundreds or thousands of samples. This chapter specifically deals with handling of large-scale plant samples for metabolomics analysis of quantitative trait loci (mQTL) in order to reduce analytical error as well as batch-to-batch variation.
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