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MRM-DIFF: data processing strategy for differential analysis in large scale MRM-based lipidomics studies.

Hiroshi Tsugawa1, Erika Ohta2, Yoshihiro Izumi2

  • 1Metabolome Informatics Research Team, Metabolomics Research Group, RIKEN Center for Sustainable Resource Science Yokohama, Japan ; Department of Biotechnology, Graduate School of Engineering, Osaka University Suita, Osaka, Japan.

Frontiers in Genetics
|February 18, 2015
PubMed
Summary

This study introduces MRM-DIFF software to automate lipid identification and quantification in large-scale lipidomics assays. The tool accelerates analysis by aligning chromatograms and correcting for isotopic peaks, reducing manual effort and errors.

Keywords:
compound identificationdifferential analysisisotopic peak estimationlipidomicsmultiple reaction monitoring

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Area of Science:

  • Metabolomics
  • Analytical Chemistry
  • Bioinformatics

Background:

  • Lipidomics studies often involve analyzing thousands of multiple reaction monitoring (MRM) transitions per run.
  • Manual identification and quantification of lipid species from MRM chromatograms are labor-intensive and prone to errors.
  • Isotopic peaks complicate accurate lipid analysis.

Purpose of the Study:

  • To develop and present novel software, MRM-DIFF, for the differential analysis of large-scale multiple reaction monitoring (MRM) assays.
  • To accelerate the identification and quantification of lipid species in lipidomics.
  • To reduce misidentification and overestimation of lipid profiles in MRM-based lipidomics research.

Main Methods:

  • Development of the MRM-DIFF software for differential analysis of MRM assays.
  • Implementation of a correlation optimized warping (COW) algorithm for MRM chromatogram alignment.
  • Utilization of quality control (QC) sample datasets for automatic alignment parameter adjustment.
  • Incorporation of user-defined reference libraries for lipid identification and isotopic peak correction.

Main Results:

  • The MRM-DIFF software successfully automates the alignment of MRM chromatograms using COW algorithm and QC data.
  • User-defined libraries enable accurate lipid identification and correction for isotopic interferences.
  • The software pipeline demonstrates reduced misidentification and overestimation of lipid profiles.

Conclusions:

  • MRM-DIFF significantly accelerates the identification and quantification of lipids in large-scale MRM assays.
  • The software provides a robust solution for differential lipidomics analysis, improving accuracy and efficiency.
  • MRM-DIFF is available for download with example datasets and tutorials.