BugSeq: a highly accurate cloud platform for long-read metagenomic analyses
| Autor: | Steven H. Huang, Jeremy Fan, Samuel D. Chorlton |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Nanopore
Computer science Sample (material) Cloud computing lcsh:Computer applications to medicine. Medical informatics computer.software_genre Microbiology Biochemistry Third-generation 03 medical and health sciences 0302 clinical medicine Species level Structural Biology Classifier (linguistics) Humans Sequencing lcsh:QH301-705.5 Molecular Biology 030304 developmental biology 0303 health sciences business.industry Applied Mathematics High-Throughput Nucleotide Sequencing Biological classification Cloud Computing Computer Science Applications Nanopore Sequencing lcsh:Biology (General) Metagenomics Scalability lcsh:R858-859.7 Metagenome Long-read Nanopore sequencing Data mining business computer Software 030217 neurology & neurosurgery |
| Zdroj: | BMC Bioinformatics BMC Bioinformatics, Vol 22, Iss 1, Pp 1-12 (2021) |
| ISSN: | 1471-2105 |
| DOI: | 10.1186/s12859-021-04089-5 |
| Popis: | Background As the use of nanopore sequencing for metagenomic analysis increases, tools capable of performing long-read taxonomic classification (ie. determining the composition of a sample) in a fast and accurate manner are needed. Existing tools were either designed for short-read data (eg. Centrifuge), take days to analyse modern sequencer outputs (eg. MetaMaps) or suffer from suboptimal accuracy (eg. CDKAM). Additionally, all tools require command line expertise and do not scale in the cloud. Results We present BugSeq, a novel, highly accurate metagenomic classifier for nanopore reads. We evaluate BugSeq on simulated data, mock microbial communities and real clinical samples. On the ZymoBIOMICS Even and Log communities, BugSeq (F1 = 0.95 at species level) offers better read classification than MetaMaps (F1 = 0.89–0.94) in a fraction of the time. BugSeq significantly improves on the accuracy of Centrifuge (F1 = 0.79–0.93) and CDKAM (F1 = 0.91–0.94) while offering competitive run times. When applied to 41 samples from patients with lower respiratory tract infections, BugSeq produces greater concordance with microbiological culture and qPCR compared with “What’s In My Pot” analysis. Conclusion BugSeq is deployed to the cloud for easy and scalable long-read metagenomic analyses. BugSeq is freely available for non-commercial use at https://bugseq.com/free. |
| Databáze: | OpenAIRE |
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