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Related Concept Videos

High-Resolution Mass Spectrometry (HRMS)01:15

High-Resolution Mass Spectrometry (HRMS)

The resolution of a mass spectrometer depends on the efficiency of separating ions with different ion masses. The mass of an atom is approximated to the sum of the masses of protons and neutrons inside, considering the masses of protons and neutrons as equal. However, the masses of the proton (1.6726 × 10−24 g) and neutron (1.6749 × 10−24 g) are not truly equal. There is a minor error in the expression of atomic masses relative to the simplest atom of hydrogen. For example, the mass of helium...

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Related Experiment Video

Updated: Jul 12, 2026

Sample Preparation for Single Cell Mass Spectrometry Metabolomics Studies: Combined Cell Washing, Quenching, Drying, and Storage
08:07

Sample Preparation for Single Cell Mass Spectrometry Metabolomics Studies: Combined Cell Washing, Quenching, Drying, and Storage

Published on: September 16, 2025

An m/z- and Intensity-Based HRMS Clustering Algorithm Targeted toward Single-Cell Metabolomics.

Dirk Wevers1, Laura Koldenhof1,2, Laura Castaneda1

  • 1Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Wassenaarseweg 76, AL Leiden 2333, The Netherlands.

Journal of the American Society for Mass Spectrometry
|July 10, 2026
PubMed
Summary
This summary is machine-generated.

A new algorithm, Global Clustering unTargeted Analysis (GCTA), improves single-cell metabolomics by accurately clustering and aligning mass spectrometry data. This advancement is crucial for developing new diagnostic tools and understanding cell biology.

Keywords:
HRMS data processingaggregationnoise filteringpeak splittingreference-free clustering and alignmentsingle-cell metabolomics

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Targeted Metabolomics on Rare Primary Cells
08:28

Targeted Metabolomics on Rare Primary Cells

Published on: February 23, 2024

Related Experiment Videos

Last Updated: Jul 12, 2026

Sample Preparation for Single Cell Mass Spectrometry Metabolomics Studies: Combined Cell Washing, Quenching, Drying, and Storage
08:07

Sample Preparation for Single Cell Mass Spectrometry Metabolomics Studies: Combined Cell Washing, Quenching, Drying, and Storage

Published on: September 16, 2025

Targeted Metabolomics on Rare Primary Cells
08:28

Targeted Metabolomics on Rare Primary Cells

Published on: February 23, 2024

Area of Science:

  • Analytical Chemistry
  • Biochemistry
  • Cell Biology

Background:

  • Single-cell (SC) metabolomics uses high-resolution mass spectrometry (HRMS) to analyze cellular components, offering potential for diagnostics and mechanistic insights.
  • Existing HRMS data processing software is not optimized for SC HRMS data, lacking necessary features for across-scan clustering and across-sample alignment of m/z values.

Purpose of the Study:

  • To present a novel, robust algorithm for SC HRMS m/z clustering and alignment.
  • To compare the performance of the new algorithm against existing commercial and open-source software.

Main Methods:

  • Development of the Global Clustering unTargeted Analysis (GCTA) algorithm, featuring strict cluster size limits and noise filtering.
  • Comparison of GCTA with Sciex MarkerView, Thermo FreeStyle, DBSCAN, and MaldiQuant binning using standard mixes and SC HRMS data from two cell lines.
  • Evaluation based on accuracy in identifying known m/z values from databases (HMDB, LipidMaps) and standard compounds.

Main Results:

  • GCTA demonstrates accuracy comparable to commercial software (MarkerView, FreeStyle) for m/z clustering and alignment.
  • The algorithm effectively filters noise and is less prone to peak splitting than MaldiQuant binning.
  • GCTA shows competitive performance against DBSCAN, MaldiQuant binning, and MarkerView when compared to theoretical m/z values.

Conclusions:

  • The developed GCTA algorithm is a pivotal tool for untargeted SC HRMS metabolomics, providing reliable compound identification and data processing.
  • GCTA's ability to perform both m/z clustering and reference-free alignment enhances its utility for advancing SC metabolomics research.