Single-molecule localisation microscopy (SMLM) has the potential to reveal the underlying
organisation of specific molecules within supramolecular complexes and their conformations,
which is not possible with conventional microscope resolution. However, the detection
efficiency for fluorescent molecules in cells can be limited in SMLM, even to below
1% in thick and dense samples. Segmentation of individual complexes can also be challenging.
To overcome these problems, we have developed a software package termed PERPL: Pattern
Extraction from Relative Positions of Localisations. This software assesses the relative
likelihoods of models for underlying patterns behind incomplete SMLM data, based on
the relative positions of pairs of localisations. We review its principles and demonstrate
its use on the 3D lattice of Z-disk proteins in mammalian cardiomyocytes. We find
known and novel features at similar to 20 nm with localisations of less than 1% of
the target proteins, using mEos fluorescent protein constructs.