Improved Mutation Detection in Duplex Sequencing Data with Sample-Specific Error Profiles.

ABSTRACT: Duplex sequencing enables highly accurate detection of rare somatic mutations, but existing variant callers often rely on protocol-specific heuristics that limit sensitivity, reproducibility, and cross-study comparability. We present DupCaller, a probabilistic variant caller that builds sample-specific error profiles and applies a strand-aware statistical model for mutation detection. Across 50 synthetic datasets, DupCaller identified 1.25-fold more single-base substitutions (SBSs) and 1.41-fold more indels than a state-of-the-art method, while exhibiting equal or better precision. In three duplex-sequenced cell lines treated with aristolochic acid, it recovered expected mutational signatures while detecting 3.5-fold more SBSs and 2.8-fold more indels. In 93 tissue samples-including neuron

SUBMITTER: Cheng Y 

PROVIDER: S-EPMC12338636 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature