Thermal Tracks: A Gaussian process-based framework for universal melting curve analysis enabling unconstrained hit identification in thermal proteome profiling experiments

TL;DR

Thermal Tracks introduces a Gaussian process-based framework for analyzing thermal proteome profiling data, enabling flexible, unbiased detection of protein stability changes, including complex and non-sigmoidal melting behaviors.

Contribution

It presents a novel GP-based method that overcomes sigmoidal curve assumptions and null distribution constraints in TPP analysis, broadening detection capabilities.

Findings

Effectively models diverse melting curves including complex profiles.

Identifies biologically relevant stability changes missed by traditional methods.

Applicable to proteome-wide perturbation studies with improved sensitivity.

Abstract

Thermal Tracks is a Python-based statistical framework for analyzing protein thermal stability data that overcomes key limitations of existing thermal proteome profiling (TPP) work-flows. Unlike standard approaches that assume sigmoidal melting curves and are constrained by empirical null distributions (limiting significant hits to approximately 5 % of data), Thermal Tracks uses Gaussian Process (GP) models with squared-exponential kernels to flexibly model any melting curve shape while generating unbiased null distributions through kernel priors. This framework is particularly valuable for analyzing proteome-wide perturbations that significantly alter protein thermal stability, such as pathway inhibitions, genetic modifications, or environmental stresses, where conventional TPP methods may miss biologically relevant changes due to their statistical constraints. Furthermore, Thermal Tracks excels at analyzing proteins with un-conventional melting profiles, including phase-separating proteins and membrane proteins, which often exhibit complex, non-sigmoidal thermal stability behaviors. Thermal Tracks is freely available from GitHub and is implemented in Python, providing an accessible and flexible tool for proteome-wide thermal profiling studies.