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BugSeq: Automated Analyses for SARS-CoV-2 Genomic Data

Enabling microbiology labs to perform automated pathogen-agnostic diagnosis, phylogenetics and more via metagenomic sequencing

Created over 1 year ago
38 Volunteers

About the Project


New pathogen-agnostic tools are needed for infectious disease diagnosis, epidemiological typing and prevention. Metagenomic sequencing (ie. sequencing all DNA/RNA in a sample) could be the answer to this challenge; however, data analysis and computational infrastructure are currently large barriers to widespread adoption (Mintzer et al, Clin Micro Infection 2019). BugSeq ( is an online bioinformatics platform empowering microbiology labs to get started with metagenomic sequencing. BugSeq automatically performs sequencing data analyses (with a focus on nanopore sequencers) and returns actionable reports (QC, sample composition, phylogenetic tree, etc.) in useful time frames.

How far along is it

We've got a working demo up! (
The demo is already processing nanopore sequencing data from real SARS-CoV-2-positive samples that have undergone nanopore metagenomic sequencing. It's currently an MVP and we need all hands on deck (funding too!) to integrate new features (see below), scale infrastructure and democratize metagenomic data analysis.

Help Needed

Tasks that need to get done

Validation of bioinformatic pipelines
- Comparison of BugSeq metagenomic classifier to alternatives examining recall/precision at different taxonomic ranks and with real SARS-CoV-2 data
- Tweaking of parameters and ordering of steps in Nextflow to improve classifier performance
- Authoring of manuscript with evaluation data

Project details

Who is already working on this

Sam Chorlton - Resident Medical Microbiologist, Bioinformatician
Josh Chorlton - Full Stack Developer
Steven Huang - Full Stack Developer Intern

Helpful links

Scientific papers demonstrating the utility and methods of nanopore metagenomic sequencing:

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