Jim Shaw

Savont improves ASV recovery from long-read amplicon sequencing with high accuracy and lower sequencing depth.

Myloasm improves metagenome assembly using long reads, recovering more complete contigs and resolving antibiotic resistance genes.

The paper presents a global virome atlas, UHGV, and identifies genomic factors influencing phage-host interactions.

divider reconstructs haplotypes from long-read sequencing data, achieving higher accuracy than existing methods on synthetic and real datasets.

Sylph is a metagenome profiler that estimates genome-to-metagenome containment ANI using k-mer statistics, outperforming Kraken2 in speed and memory usage while detecting more viral sequences in the human gut.

Floria rapidly and accurately recovers strain haplotypes from metagenomic data, outperforming existing methods in speed and strain content recovery.

Fairy provides a fast, approximate coverage calculation method for multi-sample metagenomic binning, achieving high accuracy and speed compared to read alignment.

Mora reassigns metagenomic reads to strains with high precision, outperforming other algorithms on similar reads and achieving comparable F1 scores with less runtime.

skani estimates average nucleotide identity (ANI) from sparse FracMinHash k-mer chains, staying robust to incomplete, fragmented metagenome-assembled genomes while running over 20 times faster than FastANI.

The paper provides theoretical guarantees for the seed-chain-extend heuristic in sequence alignment, showing it can achieve near-linear runtime and high accuracy with optimal k-mer size.

The paper introduces a sequence-sampling method that optimizes sensitivity for sequence comparison and improves specificity for biological DNA.

This paper introduces two new formulations for polyploid haplotype phasing and presents a method called flopp that outperforms existing algorithms in speed and accuracy.

The paper develops a theoretical framework for evaluating k-mer selection methods and demonstrates improved long-read alignment using an optimized method.

This paper introduces a hybrid metagenomic assembler that improves assembly quality and enables high-resolution analysis of resistance determinants and mobile elements in the human gut microbiome.