Lars Gustav Snipen

Benchmarking 16S rRNA gene amplicon analysis in high-diversity microbial communities reveals fundamental trade-offs in clustering and denoising

This study benchmarks 16S rRNA gene analysis pipelines in high-diversity datasets, revealing trade-offs between clustering accuracy, species recovery, and abundance reconstruction.

Rsearch: An R interface to VSEARCH supporting visualization and parameter tuning

Rsearch runs VSEARCH from R with quality plots, trimming optimizers and phyloseq conversion; on a 16S mock community it matched DADA2's abundance accuracy with fewer, more prevalent OTUs.

A Targeted Reference Database for Improved Analysis of Environmental 16S rRNA Oxford Nanopore Sequencing Data

The paper develops a targeted reference database, AQUAeD-DB, to improve taxonomic accuracy of 16S rRNA sequencing data from seafloor sediments using Oxford Nanopore Technologies.

Enhanced Prediction of Seafloor Ecological State Using 16S Nanopore Sequencing

This study compares Illumina and Nanopore 16S rRNA sequencing for predicting seafloor ecological state using machine learning and feature selection, showing comparable performance with Nanopore as a viable alternative.

A compositional reanalysis of poly(A)-selected RNA-seq reveals tank effects but no survival-associated differences

The paper analyzes unmapped reads from Atlantic salmon RNA-seq to detect microbial signals, finding tank-specific effects but no survival or sex associations.

Key roles of microbial sulfur and ammonium oxidizers for the coastal seafloor ecological state

The paper examines the relationship between microbial sulfur and ammonium oxidizers and macrofaunal state in coastal seafloor samples, finding distinct microbial networks linked to macrofauna loss or preservation.

Tracing of streptococcal strains from infant stool across human body sites links gut specificity to adhesins

The paper traces streptococcal strains from infant stool to other body sites, showing gut-specific strains are linked to adhesin gene differences.

Standardising a microbiome pipeline for body fluid identification from complex crime scene stains

This study develops a random forest classifier to identify body fluids from complex crime scene stains using microbiome data, achieving an F1 score of 0.89 on forensic samples.