RT Journal Article SR Electronic T1 3D multi-color far-red single-molecule localization microscopy with probability-based fluorophore classification JF bioRxiv FD Cold Spring Harbor Laboratory SP 2022.01.14.476290 DO 10.1101/2022.01.14.476290 A1 Siemons, Marijn E. A1 Jurriens, Daphne A1 Smith, Carlas S. A1 Kapitein, Lukas C. YR 2022 UL http://biorxiv.org/content/early/2022/01/17/2022.01.14.476290.abstract AB Single-Molecule Localization Microscopy remains limited in its ability for robust and simple multi-color imaging. Whereas the fluorophore Alexa647 is widely used due to its brightness and excellent blinking dynamics, other excellent blinking fluorophores, such as CF660 and CF680, spectrally overlap. Here we present Probability-based Fluorophore Classification, a method to perform multi-color SMLM with Alexa647, CF660 and CF680 that uses statistical decision theory for optimal classification. The emission is split in a short and long wavelength channel to enable classification and localization without a major loss in localization precision. Each emitter is classified using a Generalized Maximum Likelihood Ratio Test using the photon statistics of both channels. This easy-to-adopt approach does not require nanometer channel registration, is able to classify fluorophores with tunable low false positive rates (<0.5%) and optimal true positive rates and outperforms traditional ratiometric spectral de-mixing and Salvaged Fluorescence. We demonstrate its applicability on a variety of samples and targets.Competing Interest StatementThe authors have declared no competing interest.