Semiparametric point process modeling of blinking artifacts in PALM
Louis G. Jensen, David J. Williamson, Ute Hahn

TL;DR
This paper introduces a semiparametric point process model to correct blinking artifacts in PALM microscopy data, enabling more accurate protein clustering analysis without relying on strict parametric assumptions.
Contribution
The authors develop the PALM-IBCpp model, a novel semiparametric approach for modeling blinking artifacts in PALM data, with a flexible estimation procedure that improves quantitative analysis.
Findings
Accurately recovered ground truth in nuclear pore complex data.
Demonstrated blinking correction improves protein clustering tests.
Validated model performance through simulations with various blinking and clustering levels.
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…
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Taxonomy
TopicsPoint processes and geometric inequalities
