frcoloc
This colocalization scheme unveils statistically significant overlapping regions by identifying correlation between fluorescence color channels and clusters from unsupervised machine learning methods like hierarchical cluster analysis (HCA) performed on Raman or CARS spectral images. The scheme works as a pre-selection to gather appropriate spectra which can be used as training data to establish a supervised classifier (e.g. Random Forest) to automatically identify subcellular compartments.
A dataset for testing can be downloaded here: http://www2.rz.rub.de:8234/imperia/md/content/pure/supplement.zip
Cite: Krauß, Sascha D., et al. "Colocalization of fluorescence and Raman microscopic images for the identification of subcellular compartments: a validation study." Analyst (2015). http://dx.doi.org/10.1039/C4AN02153C
Cite As
Sascha D. Krauß (2024). frcoloc (https://www.mathworks.com/matlabcentral/fileexchange/46608-frcoloc), MATLAB Central File Exchange. Retrieved .
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getTrain/
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1.6.0.0 | Added http://dx.doi.org/10.1039/C4AN02153C
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1.5.0.0 | Added Citation. |
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1.4.0.0 | Added some comments to the source code. |
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1.3.0.0 | - New source code version, including for example different correlation coefficients.
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1.2.0.0 | Misspelling. |
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1.1.0.0 | Changed name of directory and improved description. |
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1.0.0.0 |