ArticleMetabolomics : Official journal of the Metabolomic Society2022
Spectral binning as an approach to post-acquisition processing of high resolution FIE-MS metabolome fingerprinting data.
Article in Metabolomics : Official journal of the Metabolomic Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06900270 (Cross-sectional Cohort Analysis of Plasma Proteomics in Coronary Artery Disease and Plasma Metabolomics in Coronary Artery Disease), which is not on this map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Cross-sectional Cohort Analysis of Plasma Proteomics in Coronary Artery Disease and Plasma Metabolomics in Coronary Artery Disease: Comparative Study Between Patients with Obstructive (≥ 50%), Non-obstructive (< 50%) and No Lesions
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Current data processing methods and reporting standards for untargeted analysis of volatile organic compounds using direct mass spectrometry: a systematic review.Metabolomics : Official journal of the Metabolomic Society · 2024Pooled it
- An m/z- and Intensity-Based HRMS Clustering Algorithm Targeted toward Single-Cell Metabolomics.Journal of the American Society for Mass Spectrometry · 2026Article
- Metabolic Fingerprinting of Urine Reveals Metabolite Changes in Women With Breast Cancer.Cancer medicine · 2026Article
- Chemical Attributes of UK-Grown Tea and Identifying Catechin and Metabolite Dynamics in Green and Black Tea Using Metabolomics and Machine Learning.Metabolites · 2026Article
- Resolution-Adaptive Binning Enhances Machine Learning Modeling by Interbatch and Multiplatform Orbitrap-Based Shotgun Mass Spectrometry Data Integration.Analytical chemistry · 2025Article
- Daily Consumption of Kombucha Influences the Urinary and Plasma Metabolome in a Healthy Human Cohort.Food science & nutrition · 2025Article
- Population genomics uncovers loci for trait improvement in the indigenous African cereal tef (Eragrostis tef).Communications biology · 2025Article
- Effect of Thermal Processing by Spray Drying on Key Ginger Compounds.Metabolites · 2025Article
- SARS-CoV2 variants differentially impact on the plasma metabolome.Metabolomics : Official journal of the Metabolomic Society · 2025Article
- Chemical Diversity of UK-Grown Tea Explored Using Metabolomics and Machine Learning.Metabolites · 2025Article
- Oral supplement in healthy older adults to support physical fitness and mental wellbeing.Frontiers in nutrition · 2025Article
- MassLite: An integrated python platform for single cell mass spectrometry metabolomics data pretreatment with graphical user interface and advanced peak alignment method.Analytica chimica acta · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
introductionFlow infusion electrospray high resolution mass spectrometry (FIE-HRMS) fingerprinting produces complex, high dimensional data sets which require specialist in-silico software tools to process the data prior to analysis.
objectivesPresent spectral binning as a pragmatic approach to post-acquisition procession of FIE-HRMS metabolome fingerprinting data.
methodsA spectral binning approach was developed that included the elimination of single scan m/z events, the binning of spectra and the averaging of spectra across the infusion profile. The modal accurate m/z was then extracted for each bin. This approach was assessed using four different biological matrices and a mix of 31 known chemical standards analysed by FIE-HRMS using an Exactive Orbitrap. Bin purity and centrality metrics were developed to objectively assess the distribution and position of accurate m/z within an individual bin respectively.
resultsThe optimal spectral binning width was found to be 0.01 amu. 80.8% of the extracted accurate m/z matched to predicted ionisation products of the chemical standards mix were found to have an error of below 3 ppm. The open-source R package binneR was developed as a user friendly implementation of the approach. This was able to process 100 data files using 4 Central Processing Units (CPU) workers in only 55 seconds with a maximum memory usage of 1.36 GB.
conclusionSpectral binning is a fast and robust method for the post-acquisition processing of FIE-HRMS data. The open-source R package binneR allows users to efficiently process data from FIE-HRMS experiments with the resources available on a standard desktop computer.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.