We present an algorithm, SComatic, that can be used to directly detect somatic mutations in single-cell data sets without using a reference sample. This method opens the possibility of studying clonal relationships among cells, mutational processes at single-cell resolution, and the impact of somatic mutations on cell function in development and disease.
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This is a summary of: Muyas, F. et al. De novo detection of somatic mutations in high-throughput single-cell profiling data sets. Nat. Biotechnol. https://doi.org/10.1038/s41587-023-01863-z (2023).
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Detecting somatic mutations in single-cell data sets. Nat Biotechnol (2023). https://doi.org/10.1038/s41587-023-01883-9
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DOI: https://doi.org/10.1038/s41587-023-01883-9
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