Xome-Blender: A novel cancer genome simulator

Abstract

The adoption of next generation sequencing based methods in cancer research allowed for the investigation of the complex genetic structure of tumor samples. In the last few years, considerable importance was given to the research of somatic variants and several computational approaches were developed for this purpose. Despite continuous improvements to these programs, the validation of their results it’s a hard challenge due to multiple sources of error. To overcome this drawback different simulation approaches are used to generate synthetic samples but they are often based on the addition of artificial mutations that mimic the complexity of genomic variations. For these reasons, we developed a novel software, Xome-Blender, that generates synthetic cancer genomes with user defined features such as the number of subclones, the number of somatic variants and the presence of copy number alterations (CNAs), without the addition of any synthetic element. The singularity of our method is the “morphological approach” used to generate mutation events. To demonstrate the power of our tool we used it to address the hard challenge of evaluating the performance of nine state-of-the-art somatic variant calling methods for small and large variants (VarScan2, MuTect, Shimmer, BCFtools, Strelka, EXCAVATOR2, Control-FREEC and CopywriteR). Through these analyses we observed that by using Xome-Blender data it is possible to appraise small differences between their performance and we have designated VarScan2 and EXCAVATOR2 as best tool for this kind of applications. Xome-Blender is unix-based, licensed under the GPLv3 and freely available at https://github.com/rsemeraro/XomeBlender.

Eleven grand challenges in single-cell data science

“…There are few exceptions known to us, including the tools Splatter [354], powsimR [355], and SymSim [356], which provide frameworks for simulation of scRNA-seq data and whose accuracy has been validated by comparison of its results with real data. For single-cell phylogenomics, cancer genome evolution simulators are being designed [357][358][359].…”

PGsim: A Comprehensive and Highly Customizable Personal Genome Simulator

“…SVEngine simulates structural variants in silico and provides variants with different allelic fractions and haplotypes (Xia et al, 2018). Xome-Blender generates synthetic cancer genomes with user-defined features such as the number of subclones, the number of somatic variants, and the presence of copy number alterations (Semeraro et al, 2018). Sim1000G is an R package for simulating variants in genomic regions among unrelated individuals or families using KGP data (Dimitromanolakis et al, 2019).…”

simuG: a general-purpose genome simulator

“…Simulome (Price et al , 2017) is another random variant simulator that provides finer control options, but it is designed for prokaryote genomes only. More sophisticated tools exist, such as VarSim (Mu et al , 2015) and Xome-Blender (Semeraro et al , 2018), but these tools are mostly tailored for human cancer genome simulation and often require additional third-party databases. Therefore, we feel there is need for a genome simulator that strikes a balance between simplicity and versatility.…”