SCSilicon: a tool for synthetic single-cell DNA sequencing data generation

Abstract

Background Single-cell DNA sequencing is getting indispensable in the study of cell-specific cancer genomics. The performance of computational tools that tackle single-cell genome aberrations may be nevertheless undervalued or overvalued, owing to the insufficient size of benchmarking data. In silicon simulation is a cost-effective approach to generate as many single-cell genomes as possible in a controlled manner to make reliable and valid benchmarking. Results This study proposes a new tool, SCSilicon, which efficiently generates single-cell in silicon DNA reads with minimum manual intervention. SCSilicon automatically creates a set of genomic aberrations, including SNP, SNV, Indel, and CNV. Besides, SCSilicon yields the ground truth of CNV segmentation breakpoints and subclone cell labels. We have manually inspected a series of synthetic variations. We conducted a sanity check of the start-of-the-art single-cell CNV callers and found SCYN was the most robust one. Conclusions SCSilicon is a user-friendly software package for users to develop and benchmark single-cell CNV callers. Source code of SCSilicon is available at https://github.com/xikanfeng2/SCSilicon.

CNAsim: improved simulation of single-cell copy number profiles and DNA-seq data from tumors

“…In recent years, a number of simulators have been developed to address this challenge by modeling specific aspects of the scDNA-seq pipeline. These include PSiTE ( Yang et al 2019 ), SCSsim ( Yu et al 2020 ), SCSIM ( Giguere et al 2020 ), MosaicSim ( Srivatsa et al 2022 ), SCSilicon ( Feng and Chen 2022 ), and SimSCSnTree ( Mallory and Nakhleh 2022 ). Among these, SCSIM ( Giguere et al 2020 ) and SCSsim ( Yu et al , 2020 ) generate single-cell sequencing reads assuming biases from the whole-genome amplification (WGA) process, however neither approach models the evolutionary relationships between cells or subclones.…”

“…However, CellCoal is only able to simulate SNVs and therefore cannot be used for generating CNPs. To the best of our knowledge, SCSilicon ( Feng and Chen 2022 ) is the only existing simulator that is able to generate CNPs directly. However, there are significant drawbacks to the CNPs generated using SCSilicon.…”