Kang, S., Borgsmüller, N., Valecha, M., Kuipers, J., Alves, J. M., Prado Lopez, S., Chantada, D., Beerenwinkel, N., Posada, D., & Szczurek, E. (2022). SIEVE: joint inference of single-nucleotide variants and cell phylogeny from single-cell DNA sequencing data. Genome Biology, 23, Article 248. https://doi.org/10.1186/s13059-022-02813-9
Humans; Phylogeny; Base Sequence; Sequence Analysis, DNA; DNA; Nucleotides; Acquisition bias correction; Cell phylogeny reconstruction; Finite-sites assumption; Single-cell DNA sequencing; Somatic variant calling; Statistical phylogenetic models; Triple Negative Breast Neoplasms
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Abstract:
We present SIEVE, a statistical method for the joint inference of somatic variants and cell phylogeny under the finite-sites assumption from single-cell DNA sequencing. SIEVE leverages raw read counts for all nucleotides and corrects the acquisition bias of branch lengths. In our simulations, SIEVE outperforms other methods in phylogenetic reconstruction and variant calling accuracy, especially in the inference of homozygous variants. Applying SIEVE to three datasets, one for triple-negative breast (TNBC), and two for colorectal cancer (CRC), we find that double mutant genotypes are rare in CRC but unexpectedly frequent in the TNBC samples.
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Projekt (extern):
European Union’s Horizon 2020 Polish National Science Centre SONATA BIS European Research Council (ERC) Spanish Ministry of Science and Innovation