Single Molecule Data Analysis: An Introduction

TL;DR

This paper provides an accessible overview of data analysis methods for single molecule biophysical data, covering traditional, Bayesian, non-parametric, and information theoretic approaches for researchers at all levels.

Contribution

It offers a comprehensive, beginner-friendly review of various data analysis techniques specifically tailored for single molecule experiments, highlighting their strengths and limitations.

Findings

Detailed comparison of frequentist and Bayesian methods

Introduction to non-parametric and information theoretic approaches

Guidance on selecting appropriate analysis methods

Abstract

We review methods of data analysis for biophysical data with a special emphasis on single molecule applications. Our review is intended for anyone, from student to established researcher. For someone just getting started, we focus on exposing the logic, strength and limitations of each method and cite, as appropriate, the relevant literature for implementation details. We review traditional frequentist and Bayesian parametric approaches to data analysis and subsequently extend our discussion to recent non-parametric and information theoretic methods.