Detecting brief changes in time-series data remains a major challenge in fields where short-lived states carry meaning. In single-molecule localisation microscopy, this problem is particularly acute as fluorescent molecules used to tag protein oligomers display heterogenous photophysical behaviour that can complicate photobleach step analysis; a key step in resolving nanoscale protein organisation. Existing methods often require extensive filtering or prior calibration, and can fail to accurately account for blinking or reversible dark states that may contaminate downstream analysis. In this paper, an extension to RJMCMC is proposed for change point detection with heterogeneous temporal dynamics. This approach is applied to the problem of estimating per-frame active fluorophore counts from one-dimensional integrated intensity traces derived from Fluorescence Localisation Imaging with Photobleaching (FLImP), where compound change point pair moves are introduced to better account for short-lived events known as blinking and dark states. The approach is validated using simulated and experimental data, demonstrating improved accuracy and robustness when compared with current photobleach step analysis methods and with the existing analysis approach for FLImP data. This Compound RJMCMC (CRJMCMC) algorithm performs reliably across a wide range of fluorophore counts and signal-to-noise conditions, with signal-to-noise ratio (SNR) down to 0.001 and counts as high as nineteen fluorophores, while also effectively estimating low counts observed when studying EGFR oligomerisation. Beyond single molecule imaging, this work has applications for a variety of time series change point detection problems with heterogeneous state persistence. For example, electrocorticography brain-state segmentation, fault detection in industrial process monitoring and realised volatility in financial time series.

翻译：在时间序列数据中检测短暂变化仍是短时状态具有意义领域的重大挑战。在单分子定位显微镜中，此问题尤为严峻——用于标记蛋白质低聚体的荧光分子表现出异质光物理行为，可能使光漂白台阶分析（解析纳米级蛋白质组织的关键步骤）复杂化。现有方法通常需要大量过滤或先验校准，且难以准确解释可能污染下游分析的闪烁或可逆暗态。本文提出一种面向异构时态动力学的变点检测RJMCMC扩展方法。该方法应用于从荧光定位成像-光漂白（FLImP）的一维积分强度轨迹中估计每帧活性荧光团计数的问题，通过引入复合变点对移动以更好地解释被称为闪烁和暗态的短寿命事件。利用模拟与实验数据进行验证，结果表明该方法相较于当前光漂白台阶分析方法及现有FLImP数据分析方法，在准确性与鲁棒性上均有提升。该复合RJMCMC（CRJMCMC）算法在宽范围荧光团计数（信噪比低至0.001、计数高达19个荧光团）与信噪比条件下均能可靠运行，同时有效估计研究EGFR低聚化时观测到的低计数。除单分子成像外，该工作可应用于多种具有异构状态持久性的时间序列变点检测问题，例如皮层电图脑状态分割、工业过程监控中的故障检测以及金融时间序列的实现波动率分析。