MaCADEMIA: a software toolbox for single-molecule fluorescence image quantification
- 1Biosciences Institute, Newcastle-upon-Tyne, NE2 4HH, United Kingdom
Abstract
Single-molecule localisation microscopy (SMLM) is a powerful tool in molecular and cellular biology and part of the broad umbrella of super-resolution microscopy. A distinct feature of SMLM, is its capacity for deep quantification, beyond just spatial information, to copy number, stoichiometry, molecular interaction and dynamics in living cells. The hardware required is increasingly straightforward to implement. However, complexity remains in the image analysis where much remains fragmented across specialised software tools. Here, we present MaCADEMIA (Matlab Computational Analysis of Diffusion, Emitter Molecular Intensity and Abundance), a simple yet powerful toolbox of MATLAB functions and associated documentation to enable straightforward extraction of quantitative single-molecule information. MaCADEMIA performs ensemble particle detection achieving localisation accuracies down to 0.5 pixels Root mean squared error (RMSE) across wide signal-to-noise (SNR) ranges on standardised particle tracking benchmarks, consistently matching or exceeding the performance of 14 leading methods. Our integrated workflow enables molecular counting and stoichiometry determination through stepwise photobleaching analysis, mobility measurement via mean squared displacement, colocalisaton analysis and absolute protein copy number quantification using three-dimensional cellular models.
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BibTeX
@misc{alderson2026macademia,
title = {{MaCADEMIA: a software toolbox for single-molecule fluorescence image quantification}},
author = {D. Alderson and Z. Catchpole and K. Crompton and K. Sanders and S. Johnson and K. Smith and J. Packer and K. S. Harris and J. Rodriguez and M. C. Leake and A. J. Wollman},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.30.763064},
url = {https://www.biorxiv.org/content/10.64898/2026.10.30.763064v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - MaCADEMIA: a software toolbox for single-molecule fluorescence image quantification
AU - D. Alderson
AU - Z. Catchpole
AU - K. Crompton
AU - K. Sanders
AU - S. Johnson
AU - K. Smith
AU - J. Packer
AU - K. S. Harris
AU - J. Rodriguez
AU - M. C. Leake
AU - A. J. Wollman
PY - 2026
DA - 2026/10/30
PB - bioRxiv
DO - 10.64898/2026.10.30.763064
UR - https://www.biorxiv.org/content/10.64898/2026.10.30.763064v1
AB - Single-molecule localisation microscopy (SMLM) is a powerful tool in molecular and cellular biology and part of the broad umbrella of super-resolution microscopy. A distinct feature of SMLM, is its capacity for deep quantification, beyond just spatial information, to copy number, stoichiometry, molecular interaction and dynamics in living cells. The hardware required is increasingly straightforward to implement. However, complexity remains in the image analysis where much remains fragmented across specialised software tools. Here, we present MaCADEMIA (Matlab Computational Analysis of Diffusion, Emitter Molecular Intensity and Abundance), a simple yet powerful toolbox of MATLAB functions and associated documentation to enable straightforward extraction of quantitative single-molecule information. MaCADEMIA performs ensemble particle detection achieving localisation accuracies down to 0.5 pixels Root mean squared error (RMSE) across wide signal-to-noise (SNR) ranges on standardised particle tracking benchmarks, consistently matching or exceeding the performance of 14 leading methods. Our integrated workflow enables molecular counting and stoichiometry determination through stepwise photobleaching analysis, mobility measurement via mean squared displacement, colocalisaton analysis and absolute protein copy number quantification using three-dimensional cellular models.
ER -