Sunbeam: a robust, extensible metagenomic sequencing pipeline
Sunbeam is a pipeline written in snakemake that simplifies and automates many of the steps in metagenomic sequencing analysis. It uses conda to manage dependencies, so it doesn't have pre-existing dependencies or admin privileges, and can be deployed on most Linux workstations and clusters. To read more, check out our paper in Microbiome.
Sunbeam currently automates the following tasks:
- Quality control, including adaptor trimming, host read removal, and quality filtering;
- Taxonomic assignment of reads to databases using Kraken;
- Assembly of reads into contigs using Megahit;
- Contig annotation using BLAST[n/p/x];
- Mapping of reads to target genomes; and
- ORF prediction using Prodigal.
Sunbeam was designed to be modular and extensible. Some extensions have been built for:
- IGV for viewing read alignments
- KrakenHLL, an alternate read classifier
- Kaiju, a read classifier that uses BWA rather than kmers
- Anvi'o, a downstream analysis pipeline that does lots of stuff!
More extensions can be found at the extension page: https://github.com/sunbeam-labs.
To get started, see our documentation!
If you use the Sunbeam pipeline in your research, please cite:
EL Clarke, LJ Taylor, C Zhao, A Connell, J Lee, FD Bushman, K Bittinger. Sunbeam: an extensible pipeline for analyzing metagenomic sequencing experiments. Microbiome 7:46 (2019)
See how people are using Sunbeam:
- Shi, Z et al. Segmented Filamentous Bacteria Prevent and Cure Rotavirus Infection. Cell 179, 644-658.e13 (2019).
- Abbas, AA et al. Redondoviridae, a Family of Small, Circular DNA Viruses of the Human Oro-Respiratory Tract Associated with Periodontitis and Critical Illness. Cell Host Microbe 25, 719–729 (2019).
- Leiby, JS et al. Lack of detection of a human placenta microbiome in samples from preterm and term deliveries. Microbiome 6, 1–11 (2018).
Contributors
- Erik Clarke (@eclarke)
- Chunyu Zhao (@zhaoc1)
- Jesse Connell (@ressy)
- Louis Taylor (@louiejtaylor)
- Charlie Bushman (@ulthran)
- Kyle Bittinger (@kylebittinger)