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

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

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 simulation...

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Bibliographic Details
Main Authors: Senbai Kang, Nico Borgsmüller, Monica Valecha, Jack Kuipers, Joao M. Alves, Sonia Prado-López, Débora Chantada, Niko Beerenwinkel, David Posada, Ewa Szczurek
Format: Article
Language:English
Published: BMC 2022-11-01
Series:Genome Biology
Subjects:
Single-cell DNA sequencing
Statistical phylogenetic models
Cell phylogeny reconstruction
Somatic variant calling
Finite-sites assumption
Acquisition bias correction
Online Access:https://doi.org/10.1186/s13059-022-02813-9

Internet

https://doi.org/10.1186/s13059-022-02813-9

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