ArticleBioinformatics (Oxford, England)2023
CNAsim: improved simulation of single-cell copy number profiles and DNA-seq data from tumors.
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Single-cell omics data-driven decoding of tumor clonal evolution through reinforcement learning.Genome medicine · 2026Article
- SISTEM: simulation of tumor evolution, metastasis, and DNA-seq data under genotype-driven selection.Bioinformatics (Oxford, England) · 2025Article
- CNRein: an evolution-aware deep reinforcement learning algorithm for single-cell DNA copy number calling.Genome biology · 2025Article
- DICE: fast and accurate distance-based reconstruction of single-cell copy number phylogenies.Life science alliance · 2025Article
- Improved allele-specific single-cell copy number estimation in low-coverage DNA-sequencing.Bioinformatics (Oxford, England) · 2024Article
- Article
- Assessing the merits: an opinion on the effectiveness of simulation techniques in tumor subclonal reconstruction.Bioinformatics advances · 2024Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
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Abstract
summaryCNAsim is a software package for improved simulation of single-cell copy number alteration (CNA) data from tumors. CNAsim can be used to efficiently generate single-cell copy number profiles for thousands of simulated tumor cells under a more realistic error model and a broader range of possible CNA mechanisms compared with existing simulators. The error model implemented in CNAsim accounts for the specific biases of single-cell sequencing that leads to read count fluctuation and poor resolution of CNA detection. For improved realism over existing simulators, CNAsim can (i) generate WGD, whole-chromosomal CNAs, and chromosome-arm CNAs, (ii) simulate subclonal population structure defined by the accumulation of chromosomal CNAs, and (iii) dilute the sampled cell population with both normal diploid cells and pseudo-diploid cells. The software can also generate DNA-seq data for sampled cells. AVAILABILITY AND IMPLEMENTATION: CNAsim is written in Python and is freely available open-source from https://github.com/samsonweiner/CNAsim.
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