Title: Simulating genetically heterozygous genomes in the tumour tissue according to its clonal evolution history

Authors: Yanshuo Chu; Mingxiang Teng; Yadong Wang

Addresses: School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, China ' School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, China ' School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, China

Abstract: Tumours contain multiple, genetically diverse subclonal populations of cells that have evolved from a single progenitor population. Currently, next-generation sequencing (NGS) and the third generation sequencing (TGS) have recently allowed us to develop algorithms to quantitatively dissect the extent of heterogeneity within a tumour, resolve cancer evolution history and identify the somatic variations and aneuploidy events with subclonal frequency. However, existing tumour NGS data has no ground truth annotation to validate all these NGS based tumour analysis algorithms. To benchmark these algorithms, a powerful tumour genome simulation tool which could simulate all the distinct subclonal genomes with diverse aneuploidy events and somatic variations according to the given tumour evolution history is in need. We provide a simulation package, Pysubsim-tree, which could simulate the tumour genomes according to their evolution history defined by the somatic variations and aneuploidy events. Pysubsim-tree is free, open source, available at: https://github.com/dustincys/pysubsimtree.

Keywords: somatic variations; cancer evolution history; tumour heterogeneity; tumour genome simulation.

DOI: 10.1504/IJCBDD.2019.099762

International Journal of Computational Biology and Drug Design, 2019 Vol.12 No.2, pp.143 - 152

Received: 21 Feb 2018
Accepted: 17 Jul 2018
Published online: 21 May 2019 *

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