finder-smlm 0.0.3

FINDER algorithm for SMLM

FINDER

---

by Andreas Nold and Pietro Verzelli

FINDER is a (meta)-clustering algorithm developed for Single Molecule Localization Microscopy (SMLM). It was introduced in our paper 'Unbiased choice of global clustering parameters for single-molecule localization microscopy'.

Please consider citing it:

@article{verzelli2022unbiased,
  title={Unbiased choice of global clustering parameters for single-molecule localization microscopy},
  author={Verzelli, Pietro and Nold, Andreas and Sun, Chao and Heilemann, Mike and Schuman, Erin M and Tchumatchenko, Tatjana},
  journal={Scientific Reports},
  volume={12},
  number={1},
  pages={22561},
  year={2022},
  publisher={Nature Publishing Group UK London}
}

For some examples of its usage and all the code used to generate the experiments of the paper, you can refer to this repo.

Installation

---

The simplest way to install Spektral is from PyPi:

pip install finder_smlm 

To install FINDER on Google Colab:

! pip install finder_smlm

Using FINDER

---

Using FINDER is really simple. To run the FINDER algorithm on your own localization data, add

from finder import Finder

FD      = Finder()
labels  = FD.fit(XC)
result_ = FD.selected_parameters

to your code, analogous to DBSCAN in the sklearn.cluster package. FINDER will choose global clustering parameters according to the overall noise levels / the robustness detected in the dataset.