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  3. Lipidcruncher: An Open-source Platform For Processing, Visualizing, And Analyzing Lipidomic Data.
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  3. Lipidcruncher: An Open-source Platform For Processing, Visualizing, And Analyzing Lipidomic Data.

Related Experiment Video

Shotgun Lipidomics of Rodent Tissues
11:46

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Published on: November 18, 2022

LipidCruncher: an open-source platform for processing, visualizing, and analyzing lipidomic data.

Hamed Abdi1, Yohannes A Ambaw1, Zon Weng Lai2

  • 1Cell Biology Program, Sloan Kettering Institute, New York, NY, USA.

BMC Bioinformatics
|June 4, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

LipidCruncher is a new web platform for analyzing lipidomics data. It streamlines processing, visualization, and quality control, accelerating biological insights from complex lipid profiles.

Keywords:
BioinformaticsComputational biologyLipidomicsLipidsMass spectrometryOpen-source softwarePhospholipidsScientific softwareSphingolipidsSterols

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Quantitative Analysis of the Cellular Lipidome of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Published on: March 8, 2020

Area of Science:

  • Lipidomics
  • Mass Spectrometry (MS)-based analysis
  • Bioinformatics

Background:

  • Mass spectrometry (MS)-based lipidomics generates vast datasets, requiring efficient evaluation tools.
  • Current workflows suffer from manual data handling and inadequate pre-analysis quality assessment.
  • LipidCruncher addresses these limitations with an integrated, web-based solution.

Purpose of the Study:

  • To introduce LipidCruncher, an open-source platform for processing, visualizing, and analyzing lipidomic data.
  • To enhance efficiency and rigor in lipidomics data analysis.
  • To bridge the gap between data generation and biological interpretation.

Main Methods:

  • Development of LipidCruncher, an open-source, web-based platform.
  • Integration of data standardization, normalization, and quality control steps.
  • Implementation of advanced visualization and analysis tools tailored for lipidomics.

    • Main Results:

    • LipidCruncher consolidates essential lipidomics analysis steps, including standardization, normalization, and quality controls.
    • The platform offers advanced tools for detailed and holistic data exploration.
    • Demonstrated utility through analysis of lipidomic data from DGAT1/DGAT2 deficient mouse adipose tissue.

    Conclusions:

    • LipidCruncher provides an integrated, quality-focused solution for lipidomics data analysis.
    • It complements existing specialized tools and accepts data from multiple sources.
    • Facilitates rigorous lipidomics analyses to accelerate biological interpretation of lipid profiles.