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Quantifying colocalization: The case for discarding the Manders overlap coefficient.

Jeremy Adler1, Ingela Parmryd1

  • 1Department of Medical Biochemistry and Cell Biology, University of Gothenburg, Gothenburg, Sweden.

Cytometry. Part a : the Journal of the International Society for Analytical Cytology
|March 15, 2021
PubMed
Summary
This summary is machine-generated.

The Manders overlap coefficient (MOC) for colocalization measurement is confusing and should be discarded. Researchers should instead report separate co-occurrence and correlation coefficients for accurate molecular distribution analysis.

Keywords:
MOCco-occurrencecolocalization analysiscorrelationfluorescencequantification

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Area of Science:

  • Microscopy and Imaging
  • Cell Biology
  • Biophysics

Background:

  • Colocalization analysis quantifies the relative distribution of molecules in biological samples.
  • The Manders overlap coefficient (MOC) is widely used but has ambiguous interpretations in literature.
  • Existing interpretations of MOC include co-occurrence, correlation, or a combination of both.

Purpose of the Study:

  • To investigate the interpretations and limitations of the Manders overlap coefficient (MOC).
  • To determine if MOC can reliably differentiate various colocalization patterns.
  • To propose an improved approach for quantifying molecular colocalization.

Main Methods:

  • Mathematical testing of the Manders overlap coefficient (MOC) equation.
  • Simulations involving different molecular intensity distributions (Gaussian, gamma, uniform, exponential).
  • Analysis of MOC's response to variations in co-occurrence and correlation.

Main Results:

  • The Manders overlap coefficient (MOC) is sensitive to both co-occurrence and correlation.
  • Varying intensity distributions significantly alter the balance between co-occurrence and correlation contributions to MOC.
  • A single MOC value can correspond to multiple, distinct colocalization scenarios, limiting its specificity.

Conclusions:

  • The Manders overlap coefficient (MOC) has limited ability to characterize specific colocalization patterns due to its ambiguity.
  • The MOC causes significant confusion and lacks a clear role in accurate colocalization measurement.
  • Recommend reporting separate co-occurrence and correlation coefficients for precise molecular distribution analysis.