Statistical analysis of fluorescence correlation spectroscopy: the standard deviation and bias

Area of Science:

• Physical Chemistry
• Biophysics
• Spectroscopy

Background:

• Fluorescence Correlation Spectroscopy (FCS) is a powerful technique for studying molecular dynamics.
• Accurate statistical analysis is crucial for reliable FCS data interpretation.
• Existing methods may not fully account for all noise sources or experimental biases.

Purpose of the Study:

• To provide a comprehensive analytical framework for FCS data analysis across various timescales.
• To identify and characterize all significant noise sources in FCS measurements.
• To develop methods for correcting experimental bias in FCS correlation functions.

Main Methods:

• Detailed analytical derivation of statistical properties of FCS data.
• Investigation of signal-to-noise ratio dependence on experimental parameters.
• Characterization of shot noise, molecular dynamics noise, and a newly identified
• particle noise
• at large lag times.

Main Results:

• Analytical calculation of standard deviations for correlation function points, showing good agreement with experimental data.
• Identification and description of
• particle noise
• governed by particle exchange at large dwell times.
• Development of a phase diagram illustrating the significance of bias in FCS experiments.

Conclusions:

• The presented analytical approach offers a robust tool for planning and analyzing FCS experiments.
• Understanding and correcting for particle noise and experimental bias are essential for accurate FCS results.
• The findings enable first-order correction of experimental correlation functions, enhancing data reliability.