Abstract
Photoactivated localization microscopy (PALM) is a powerful imaging technique for characterization of protein organization in biological cells. Due to the stochastic blinking of fluorescent probes and camera discretization effects, each protein gives rise to a cluster of artificial observations. These blinking artifacts are an obstacle for quantitative analysis of PALM data, and tools for their correction are in high demand. We develop the independent blinking cluster point process (IBCpp) family of models, which is suited for modeling of data from single-molecule localization microscopy modalities, and we present results on the mark correlation function. We then construct the PALM-IBCpp, a semiparametric IBCpp tailored for PALM data, and we describe a procedure for estimation of parameters which can be used without parametric assumptions on the spatial organization of proteins. Our model is validated on nuclear pore complex reference data, where the ground truth was accurately recovered, and we demonstrate how the estimated blinking parameters can be used to perform a blinking corrected test for protein clustering in a cell expressing the adaptor protein LAT. Finally, we consider simulations with varying degrees of blinking and protein clustering to shed light on the expected performance in a range of realistic settings.
| Original language | English |
|---|---|
| Journal | The Annals of Applied Statistics |
| Volume | 16 |
| Issue | 3 |
| Pages (from-to) | 1500-1523 |
| Number of pages | 24 |
| ISSN | 1932-6157 |
| DOIs | |
| Publication status | Published - Sept 2022 |
Keywords
- Photoactivated localization microscopy
- mark correlation function
- moment-based estimation
- multiple blinking
- second-order characteristics
- spatiotemporal point patterns
- LOCALIZATION MICROSCOPY
- MOLECULES