Jasmijn A. Baaijens

ReSeT selects reference genomes by optimizing taxonomic discrimination and representativeness, improving profiling accuracy in high-ambiguity datasets.

This study benchmarks how reference genome selection affects taxonomic profiling accuracy across bacterial and viral datasets, showing context-dependent impacts on accuracy and computational efficiency.

The paper evaluates nine computational tools for identifying SARS-CoV-2 lineages in wastewater sequencing data using simulated samples, finding most tools reliably detect lineages above 5% frequency.

ORCA predicts replication origins in prokaryotic chromosomes using nucleotide disparities, dnaA-box regions, and gene positions, with a random forest classifier.

AmpliDiff identifies discriminatory genomic regions and primers for accurate lineage abundance estimation in viral metagenomes, comparable to whole genome sequencing.

VG-Flow enables strain-aware full-length genome assembly from mixed samples using a de novo approach that improves contiguity and haplotype abundance estimation.

The paper introduces a method for full-length de novo viral quasispecies assembly using variation graphs, improving contiguity and accuracy over existing methods.

POLYTE generates haplotype-resolved de novo assemblies for diploid and polyploid genomes using an overlap graph-based method, outperforming existing approaches in accuracy and efficiency.

SAVAGE reconstructs individual haplotypes of intrahost viral strains without a reference genome, outperforming existing methods on simulated and real data.