ArticleMetabolomics : Official journal of the Metabolomic Society
A batch correction method for liquid chromatography-mass spectrometry data that does not depend on quality control samples.
Article in Metabolomics : Official journal of the Metabolomic Society. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed.
- The Impact of Milk on Gut Permeability, Fecal 16S rRNA Gene Microbiota Profiling, and Fecal Metabolomics in Children with Moderate Malnutrition in Sierra Leone: A Double-Blind, Randomized Controlled Trial.The American journal of clinical nutrition · 2024Trial
- Non-volatile metabolomic differentiation of geographical origin and quality grade in pre-Qingming Xihu Longjing green tea using in-source fragment ion-assisted annotation.Food chemistry: X · 2026Article
- Genome-wide analysis of 439 mass spectrometry-based proteomic profiles in a population of 15,035 Scottish individuals.Nature communications · 2026Article
- Gut microbiota regulates growth retardation in pigs through their metabolites of taurine and butyric acids.Frontiers in microbiology · 2026Article
- Sphingolipids as indicators of exposure to long-term air pollution: a targeted metabolomics approach.Scientific reports · 2025Article
- Methylome-wide association studies and epigenetic biomarker development for 133 mass spectrometry-assessed circulating proteins in 14,671 Generation Scotland participants.Genome biology · 2025Article
- A homoeostatic switch causing glycerol-3-phosphate and phosphoethanolamine accumulation triggers senescence by rewiring lipid metabolism.Nature metabolism · 2024Article
- Extensive identification of serum metabolites related to microbes in different gut locations and evaluating their associations with porcine fatness.Microbial biotechnology · 2023Article
- Small molecule biomarker discovery: Proposed workflow for LC-MS-based clinical research projects.Journal of mass spectrometry and advances in the clinical lab · 2023Review
- Habituation to Livestock Trailer and Its Influence on Stress Responses during Transportation in Goats.Animals : an open access journal from MDPI · 2023Article
- Regularized adversarial learning for normalization of multi-batch untargeted metabolomics data.Bioinformatics (Oxford, England) · 2023Article
- Evaluation and correction of injection order effects in LC-MS/MS based targeted metabolomics.Journal of chromatography. B, Analytical technologies in the biomedical and life sciences · 2022Article
- Following Roux-en-Y gastric bypass surgery, serum ceramides demarcate patients that will fail to achieve normoglycemia and diabetes remission.Med (New York, N.Y.) · 2022Article
- Normalizing and Correcting Variable and Complex LC-MS Metabolomic Data with the R Package pseudoDrift.Metabolites · 2022Article
- Metabolomic exploration of the effects of habituation to livestock trailer and extended transportation in goats.Frontiers in molecular biosciences · 2022Article
- Inferring early-life host and microbiome functions by mass spectrometry-based metaproteomics and metabolomics.Computational and structural biotechnology journal · 2022Review
- DBnorm as an R package for the comparison and selection of appropriate statistical methods for batch effect correction in metabolomic studies.Scientific reports · 2021Article
- Identification of the relationship between the gut microbiome and feed efficiency in a commercial pig cohort.Journal of animal science · 2021Article
- Targeted Metabolomic Assessment of the Sub-Lethal Toxicity of Halogenated Acetic Acids (HAAs) toMetabolites · 2021Article
- MEK inhibition reprograms CD8Nature immunology · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The need for reproducible and comparable results is of increasing importance in non-targeted metabolomic studies, especially when differences between experimental groups are small. Liquid chromatography-mass spectrometry spectra are often acquired batch-wise so that necessary calibrations and cleaning of the instrument can take place. However this may introduce further sources of variation, such as differences in the conditions under which the acquisition of individual batches is performed. Quality control (QC) samples are frequently employed as a means of both judging and correcting this variation. Here we show that the use of QC samples can lead to problems. The non-linearity of the response can result in substantial differences between the recorded intensities of the QCs and experimental samples, making the required adjustment difficult to predict. Furthermore, changes in the response profile between one QC interspersion and the next cannot be accounted for and QC based correction can actually exacerbate the problems by introducing artificial differences. "Background correction" methods utilise all experimental samples to estimate the variation over time rather than relying on the QC samples alone. We compare non-QC correction methods with standard QC correction and demonstrate their success in reducing differences between replicate samples and their potential to highlight differences between experimental groups previously hidden by instrumental variation.
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