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Analysis of iTRAQ data using Mascot and Peaks quantification algorithms.

Carla M R Lacerda1, Lei Xin, Iain Rogers

  • 1Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, CO 80523, USA.

Briefings in Functional Genomics & Proteomics
|April 9, 2008
PubMed
Summary

This study compares Mascot and Peaks software for protein quantification using iTRAQ data. Peaks software showed significantly higher accuracy than Mascot, highlighting critical differences in quantification algorithms for proteomics analysis.

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Area of Science:

  • Proteomics
  • Mass Spectrometry
  • Bioinformatics

Background:

  • The rapid advancement of proteomics necessitates robust protein quantification methods.
  • A limited number of analytical tools can interpret data from diverse mass spectrometers.
  • Isotope Tagging for Relative and Absolute Quantitation (iTRAQ) is a common labeling technique.

Purpose of the Study:

  • To compare the performance of Mascot and Peaks software packages for iTRAQ data analysis.
  • To evaluate the accuracy and reliability of protein quantification by these two software packages.
  • To identify discrepancies in peptide and protein quantification algorithms.

Main Methods:

  • Analysis of iTRAQ data generated from Electrospray Ionization Quadrupole Time-of-Flight (ESI-Q/TOF) mass spectrometry.

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  • Utilizing a six-protein mixture with known proportions to assess quantification accuracy.
  • Applying both Mascot and Peaks software to analyze complex protein samples.

    • Main Results:

    • The Peaks algorithm exhibited an average deviation of 14% from the correct quantification in a controlled mixture.
    • The Mascot software demonstrated a quantification error approaching 200% in the same controlled mixture.
    • For complex samples, quantification results from Mascot and Peaks agreed within 20% for only 26% of proteins.

    Conclusions:

    • Significant differences exist between Mascot and Peaks quantification algorithms.
    • The choice of software critically impacts the accuracy of iTRAQ-based protein quantification.
    • Further development is needed to address intricacies in peptide and protein quantification software.