Projects

Arx / OpenGenomeBrowser

The Problem: Today, sequencing of microbial genomes is cheap. However, extracting biological insights from this data is often hampered by a lack of tools that are scalable, interactive, and accessible to all researchers. Biologists need a way to easily manage, visualize, and query their data without deep computational expertise.

Our Approach: We developed OpenGenomeBrowser (now called Arx and developed by the startup Abrinca Genomics), a scalable, dataset-independent web platform for interactive genome data management and visualization. The platform is designed to bridge the gap between raw genomic data and actionable biological insights. It won the 2023 SIB Innovative Resource Award.

Autocycler Express

The Problem: Generating perfect, complete bacterial genome assemblies from long-read sequencing data is challenging. Automated assemblers often make errors like duplicating plasmids or failing to circularize sequences. While manual curation tools exist, they are typically labor-intensive and require command-line expertise, creating a bottleneck as sequencing output grows.

Our Approach: Autocycler Express is a browser-based user interface that streamlines and simplifies the manual curation of genome assemblies using the Autocycler pipeline. It allows for a rapid, iterative process of visualizing assembly graphs, identifying contigs (e.g., via BLAST), removing bad clusters, and cleaning the graph. This approach empowers biologists without programming skills to participate in the curation process, dramatically reducing manual effort while achieving high-quality, closed genomes ready for submission.

Scoary2: Scalable Microbial GWAS

The Problem: The functions of 40–60% of bacterial genes are unknown. Microbial genome-wide association studies (mGWAS) are a key method to link traits to genes and discover their function. However, existing tools were not designed to analyze the thousands of traits (e.g., from mass spectrometry) generated by high-throughput experiments.

Our Approach: To address this bottleneck, we developed Scoary2. It is a complete rewrite of its popular predecessor, designed for significantly improved performance, and, crucially, an interactive data exploration app. Thanks to these innovations, Scoary2 is the first tool that enables the robust and scalable study of large phenotypic datasets using mGWAS.