Large-scale untargeted LC-MS metabolomics data correction using between-batch feature alignment and cluster-based within-batch signal intensity drift correction.
Journal article, 2016

Liquid chromatography-mass spectrometry (LC-MS) is a commonly used technique in untargeted metabolomics owing to broad coverage of metabolites, high sensitivity and simple sample preparation. However, data generated from multiple batches are affected by measurement errors inherent to alterations in signal intensity, drift in mass accuracy and retention times between samples both within and between batches. These measurement errors reduce repeatability and reproducibility and may thus decrease the power to detect biological responses and obscure interpretation.

Author

Carl Brunius

Chalmers, Biology and Biological Engineering, Food and Nutrition Science

Lin Shi

Chalmers, Biology and Biological Engineering, Food and Nutrition Science

Rikard Landberg

Chalmers, Biology and Biological Engineering, Food and Nutrition Science

Metabolomics

1573-3882 (ISSN) 1573-3890 (eISSN)

Vol. 12 11 173- 173

Areas of Advance

Life Science Engineering

Subject Categories

Nutrition and Dietetics

DOI

10.1007/s11306-016-1124-4

PubMed

27746707

More information

Created

10/8/2017