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Genotyping tumor clones from single-cell data

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A new statistical approach mitigates technical errors in single-cell DNA sequencing data to advance the study of tumor evolution and diversity.

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Figure 1: Technical errors can lead to incorrect results for clonal genotypes and lineages.

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Acknowledgements

This work was supported by the Eric & Liz Lefkofsky Family Foundation, NCI (1R01CA169244-01 to N.E.N., R01CA172652 to K.C.) and the American Cancer Society (129098-RSG-16-092-01-TBG to N.E.N.). N.E.N. and K.C. are Andrew Sabin Family Fellows. The study was supported by the MD Anderson Cancer Moonshot Knowledge Gap Award and the Center for Genetics & Genomics.

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Authors and Affiliations

  1. Nicholas E. Navin is at the Department of Genetics and the Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.,

    Nicholas E Navin

  2. Ken Chen is at the Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.,

    Ken Chen

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  1. Nicholas E Navin
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  2. Ken Chen
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Correspondence to Nicholas E Navin.

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Navin, N., Chen, K. Genotyping tumor clones from single-cell data. Nat Methods 13, 555–556 (2016). https://doi.org/10.1038/nmeth.3903

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