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bioRxiv · 10.1101/2022.05.30.493957

LOMAR: LOcalization Microscopy Analysis in R

Theiss, M.·Brazma, A.·Uhlmann, V.·Heriche, J.-K.
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Abstract

In single molecule localization microscopy data (SMLM), individual instances of a macromolecular complex come in the form of point sets. Particle averaging, which combines localization data from a large number of instances, is often used to overcome experimental noise and obtain a refined view of the underlying structure. However, SMLM point sets are often heterogeneous due to biological variations in the structure they represent and must be partitioned into groups with similar structure before averaging which calls for being able to compute structurally-relevant similarity measures between sets of points. Here we introduce LOMAR (LOcalization Microscopy Analysis in R) a software package for the R programming language that enables comparison of point sets through implementation of several point sets registration methods and similarity measures derived from topological data analysis. We demonstrate use of the package on real and simulated SMLM data of nuclear pore complexes.

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Theiss, M., Brazma, A., Uhlmann, V., Heriche, J.-K.. 2022-05-30. LOMAR: LOcalization Microscopy Analysis in R. https://doi.org/10.1101/2022.05.30.493957

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