ArticleAnalytical chemistry2019
Systematic Error Removal Using Random Forest for Normalizing Large-Scale Untargeted Lipidomics Data.
Article in Analytical chemistry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 188 papers.
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Who cites it
188 citing papers in PubMed.
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- Age and sex are associated with the plasma lipidome: findings from the GOLDN study.Lipids in health and disease · 2021Trial
- Impact of Daily Preventive Zinc or Therapeutic Zinc Supplementation for Diarrhea on Plasma Biomarkers of Environmental Enteric Dysfunction among Rural Laotian Children: A Randomized Controlled Trial.The American journal of tropical medicine and hygiene · 2020Trial
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- Early pregnancy metabolomic signatures for child growth trajectories: a prospective metabolome-wide association study.The American journal of clinical nutrition · 2026Article
- A protocol for untargeted metabolomics using anion-exchange chromatography and high-resolution mass spectrometry.STAR protocols · 2026Article
- Metabolic biomarkers of treatment-resistant schizophrenia and cognitive correlates: insights from a machine learning.Molecular psychiatry · 2026Article
- Identification of Age-Associated Circulating Proteins and Lipids in 3800 Comorbidity-Enriched Older Adults from Japan-Based Cohorts Using Olink Assays and MRM Mass Spectrometry.Journal of proteome research · 2026Article
- Untargeted Blubber Metabolomics Reveals Biochemical Signatures Associated with Physiological Status in Live, Free-Ranging Bottlenose Dolphins.Metabolites · 2026Article
- Multi-Tissue Metabolomic Signatures of Five Longevity Interventions Converge on Ergothioneine and Lipid Remodeling in Male UM-HET3 Mice.bioRxiv : the preprint server for biology · 2026Article
- Identification of Circulating Lipidomic Biomarkers of Malnutrition Risk among Oncology Patients in the Total Cancer Care (TCC) Study: A Cross-Sectional Analysis.The Journal of nutrition · 2026Article
- Robust Metabolomics Data Normalization across Scales and Experimental Designs.Analytical chemistry · 2026Article
- Partial body mass regain attenuates lipid utilization and alters the hepatic lipidome linked to HDL dysfunction during metabolic syndrome in male rats.Physiological reports · 2026Article
- Parametric hypothesis testing for pathway based hierarchical structural component models.Genes & genomics · 2026Article
- Lipidomic Markers of Tobacco Use and Cessation Associated With Cardiovascular Risk Factors: A Longitudinal Study in American Indian Individuals.Journal of the American Heart Association · 2026Article
128 more citing papers are in PubMed but not listed here.
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Authors and funding
10 authors.
Funding
Abstract
Large-scale untargeted lipidomics experiments involve the measurement of hundreds to thousands of samples. Such data sets are usually acquired on one instrument over days or weeks of analysis time. Such extensive data acquisition processes introduce a variety of systematic errors, including batch differences, longitudinal drifts, or even instrument-to-instrument variation. Technical data variance can obscure the true biological signal and hinder biological discoveries. To combat this issue, we present a novel normalization approach based on using quality control pool samples (QC). This method is called systematic error removal using random forest (SERRF) for eliminating the unwanted systematic variations in large sample sets. We compared SERRF with 15 other commonly used normalization methods using six lipidomics data sets from three large cohort studies (832, 1162, and 2696 samples). SERRF reduced the average technical errors for these data sets to 5% relative standard deviation. We conclude that SERRF outperforms other existing methods and can significantly reduce the unwanted systematic variation, revealing biological variance of interest.
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