SIEVE: joint inference of single-nucleotide variants and cell phylogeny from single-cell DNA sequencing data

• Published in: Genome Biology Vol. 23; no. 1; pp. 248 - 33
• Main Authors: Kang, Senbai, Borgsmüller, Nico, Valecha, Monica, Kuipers, Jack, Alves, Joao M, Prado-López, Sonia, Chantada, Débora, Beerenwinkel, Niko, Posada, David, Szczurek, Ewa
• Format: Journal Article
• Language: English
• Published: England BioMed Central 30.11.2022; BMC
• Subjects: Acquisition bias correction; Base Sequence; Bias; Cell phylogeny reconstruction; Colorectal carcinoma; Conserved sequence; DNA; DNA sequencing; Finite-sites assumption; Genotype & phenotype; Genotypes; Humans; Method; Mutation; Nucleotide sequence; Nucleotides; Phylogenetics; Phylogeny; Sequence Analysis, DNA; Single-cell DNA sequencing; Somatic variant calling; Statistical analysis; Statistical methods; Statistical phylogenetic models; Triple Negative Breast Neoplasms; Acquisition bias correction; Statistical phylogenetic models; Finite-sites assumption; Cell phylogeny reconstruction; Somatic variant calling; Single-cell DNA sequencing
• ISSN: 1474-760X; 1474-7596; 1474-760X
• DOI: 10.1186/s13059-022-02813-9

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.