BMC Bioinformatics (Aug 2022)

SCONCE2: jointly inferring single cell copy number profiles and tumor evolutionary distances

  • Sandra Hui,
  • Rasmus Nielsen

DOI
https://doi.org/10.1186/s12859-022-04890-w
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 23

Abstract

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Abstract Background Single cell whole genome tumor sequencing can yield novel insights into the evolutionary history of somatic copy number alterations. Existing single cell copy number calling methods do not explicitly model the shared evolutionary process of multiple cells, and generally analyze cells independently. Additionally, existing methods for estimating tumor cell phylogenies using copy number profiles are sensitive to profile estimation errors. Results We present SCONCE2, a method for jointly calling copy number alterations and estimating pairwise distances for single cell sequencing data. Using simulations, we show that SCONCE2 has higher accuracy in copy number calling and phylogeny estimation than competing methods. We apply SCONCE2 to previously published single cell sequencing data to illustrate the utility of the method. Conclusions SCONCE2 jointly estimates copy number profiles and a distance metric for inferring tumor phylogenies in single cell whole genome tumor sequencing across multiple cells, enabling deeper understandings of tumor evolution.

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