BugSeq: Automated Analyses for SARS-CoV-2 Genomic Data
Enabling microbiology labs to perform automated pathogen-agnostic diagnosis, phylogenetics and more via metagenomic sequencing
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 (bugseq.com) 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.
We've got a working demo up! (https://bugseq.com)
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.
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
- Who is already working on this
- Helpful links
- How to get in touch
- Number of volunteers needed
- Preferred Volunteer location
- Organization status