Denoising sparse microbial signals from single-cell sequencing of mammalian host tissues

Ghaddar, B.; Blaser, M. J.; De, S.

doi:10.1101/2022.06.29.498176

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bioRxiv · 10.1101/2022.06.29.498176

Denoising sparse microbial signals from single-cell sequencing of mammalian host tissues

Ghaddar, B.·Blaser, M. J.·De, S.

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Abstract

We developed SAHMI, a computational resource to identify truly present microbial nucleic acids and filter contaminants and spurious false-positive taxonomic assignments from standard transcriptomic sequencing of mammalian tissues. In benchmark studies, SAHMI correctly identifies known microbial infections present in diverse tissues. The application of SAHMI to single-cell and spatial genomic data enables co-detection of somatic cells and microorganisms and joint analysis of host-microbiome ecosystems.

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Ghaddar, B., Blaser, M. J., De, S.. 2022-06-30. Denoising sparse microbial signals from single-cell sequencing of mammalian host tissues. https://doi.org/10.1101/2022.06.29.498176

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