MRDadaptis: self-adaptive parameter configuration enhances minimal residual disease detection in heterogeneous ctDNA samples.

ABSTRACT: Detection of structural variations (SVs) through circulating tumor DNA (ctDNA) has become a key method for detecting minimal residual disease (MRD). However, the heterogeneity of ctDNA samples, characterized by variable limits of detection (LOD) and diverse structural variant types, significantly impacts detection stability and performance, posing persistent challenges for conventional SV detection tools such as Delly and Manta. These widely used methods require extensive manual parameter tuning, hindered by the combinatorial complexity of multiple parameters and heterogeneous sequencing data. To address this, we propose MRDadaptis, a novel SV detection tool that uniquely incorporates a self-adaptive parameter optimization mechanism. MRDadaptis distinguishes itself by integrating Bayesian

SUBMITTER: Wang T 

PROVIDER: S-EPMC12527258 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature