bioRxiv · 10.1101/2025.06.20.660799
Scalable single-cell metagenomic analysis with Bascet and Zorn
Abstract
Single-cell metagenomic sequencing (scMetaG) can provide maximum-resolution insights into complex microbial communities. However, existing bioinformatic tools are not equipped to handle the massive amounts of data generated by novel high-throughput scMetaG methods. Here, we present a bioinformatic toolkit for complete, end-to-end scMetaG analysis: (i) Bascet, a command-line suite designed to scale to massive scMetaG datasets ([≥]1 million cells); (ii) Zorn, an R package/workflow manager that enables reproducible scMetaG data analysis, exploration, and visualization (http://zorn.henlab.org/). Enabled by recent advances in droplet microfluidics, we use Bascet and Zorn to develop and optimize a high-throughput scMetaG method on a ten-species mock community. To showcase their utility on a real-world sample, we use Bascet and Zorn to characterize a human saliva sample, generating single-amplified genomes (SAGs) from >10k prokaryotic cells. Overall, Bascet and Zorn enable reproducible scMetaG analysis, allowing users to query microbiomes at unprecedented resolution and scale.
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Gourle, H., Yakovenko, I., Verma, J., Dicken, J., Albrecht, F., Mazutis, L., Normark, J., Sheng, N., Strömberg, N., Löfstedt, T., Carroll, L. M., Henriksson, J. M.. 2025-06-21. Scalable single-cell metagenomic analysis with Bascet and Zorn. https://doi.org/10.1101/2025.06.20.660799
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