Integrating opportunities and parametrized signatures for improved mutational processes estimation in extended sequence contexts

TL;DR

This paper enhances mutational signature estimation by integrating opportunities, extended sequence contexts, a Negative Binomial model, and parametrized signatures, resulting in more robust and reliable results.

Contribution

It introduces a combined framework incorporating four extensions to improve the robustness of mutational signature estimation in extended sequence contexts.

Findings

Inclusion of opportunities improves signature robustness.

Parametrizing signatures enhances estimation accuracy.

Combining extensions yields more reliable mutational signatures.

Abstract

Mutational signatures describe the pattern of mutations over the different mutation types. Each mutation type is determined by a base substitution and the flanking nucleotides to the left and right of that base substitution. Due to the widespread interest in mutational signatures, several efforts have been devoted to the development of methods for robust and stable signature estimation. Here, we combine various extensions of the standard framework to estimate mutational signatures. These extensions include (a) incorporating opportunities to the analysis, (b) allowing for extended sequence contexts, (c) using the Negative Binomial model, and (d) parametrizing the signatures. We show that the combination of these four extensions gives very robust and reliable mutational signatures. In particular, we highlight the importance of including mutational opportunities and parametrizing the signatures when the mutation types describe an extended sequence context with two or three flanking nucleotides to each side of the base substitution.