Reference-Free Variant Calling with Local Graph Construction with ska lo (SKA).

ABSTRACT: The study of genomic variants is increasingly important for public health surveillance of pathogens. Traditional variant-calling methods from whole-genome sequencing data rely on reference-based alignment, which can introduce biases and require significant computational resources. Alignment- and reference-free approaches offer an alternative by leveraging k-mer-based methods, but existing implementations often suffer from sensitivity limitations, particularly in high mutation density genomic regions. Here, we present ska lo, a graph-based algorithm that aims to identify within-strain variants in pathogen whole-genome sequencing data by traversing a colored De Bruijn graph and building variant groups (i.e. sets of variant combinations). Through in silico benchmarking and real-world dataset

SUBMITTER: Derelle R 

PROVIDER: S-EPMC11986325 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature