DCSMAP: A Hybrid Linear-Pangenome Framework for Accurate and Efficient Read Alignment
Background: Linear-reference read alignment is computationally efficient but is susceptible to reference bias, whereas pangenome graph alignment better represents genetic diversity at substantially greater computational cost. Findings: We developed DCSMAP, a hybrid workflow that combines linear alignment with machine-learning-based selection of reads for remapping to a personalized pangenome…
We haven't written up this one. bioRxiv has the full story — the link below goes straight to it.
