KMS Of Academy of mathematics and systems sciences, CAS
BiTSC2: Bayesian inference of tumor clonal tree by joint analysis of single-cell SNV and CNA data | |
Chen, Ziwei3; Gong, Fuzhou2,4; Wan, Lin2,4; Ma, Liang1 | |
2022-04-02 | |
发表期刊 | BRIEFINGS IN BIOINFORMATICS |
ISSN | 1467-5463 |
页码 | 12 |
摘要 | The rapid development of single-cell DNA sequencing (scDNA-seq) technology has greatly enhanced the resolution of tumor cell profiling, providing an unprecedented perspective in characterizing intra-tumoral heterogeneity and understanding tumor progression and metastasis. However, prominent algorithms for constructing tumor phylogeny based on scDNA-seq data usually only take single nucleotide variations (SNVs) as markers, failing to consider the effect caused by copy number alterations (CNAs). Here, we propose BiTSC2, Bayesian inference of Tumor clonal Tree by joint analysis of Single-Cell SNV and CNA data. BiTSC2 takes raw reads from scDNA-seq as input, accounts for the overlapping of CNA and SNV, models allelic dropout rate, sequencing errors and missing rate, as well as assigns single cells into subclones. By applying Markov Chain Monte Carlo sampling, BiTSC2 can simultaneously estimate the subclonal scCNA and scSNV genotype matrices, subclonal assignments and tumor subclonal evolutionary tree. In comparison with existing methods on synthetic and real tumor data, BiTSC2 shows high accuracy in genotype recovery, subclonal assignment and tree reconstruction. BiTSC2 also performs robustly in dealing with scDNA-seq data with low sequencing depth and variant missing rate. BiTSC2 software is available at https://github.com/ucasdp/BiTSC2. |
关键词 | single-cell DNA sequencing intra-tumor heterogeneity single nucleotide variation copy number alteration Bayesian modeling cancer evolution |
DOI | 10.1093/bib/bbac092 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China[2019YFA0709501] ; National Key Research and Development Program of China[2018YFB0704304] ; National Natural Science Foundation of China[11971459] ; National Natural Science Foundation of China[12071466] ; National Center for Mathematics and Interdisciplinary Sciences (NCMIS) of Chinese Academy of Sciences ; Key Laboratory of Systems and Control (LSC) of Chinese Academy of Sciences |
WOS研究方向 | Biochemistry & Molecular Biology ; Mathematical & Computational Biology |
WOS类目 | Biochemical Research Methods ; Mathematical & Computational Biology |
WOS记录号 | WOS:000785832000001 |
出版者 | OXFORD UNIV PRESS |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.amss.ac.cn/handle/2S8OKBNM/60305 |
专题 | 应用数学研究所 系统科学研究所 |
通讯作者 | Wan, Lin; Ma, Liang |
作者单位 | 1.Chinese Acad Sci, Inst Zool, Key Lab Zool Systemat & Evolut, Beijing 100101, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Natl Ctr Math & Interdisciplinary Sci, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China 4.Univ Chinese Acad Sci, Sch Math Sci, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Chen, Ziwei,Gong, Fuzhou,Wan, Lin,et al. BiTSC2: Bayesian inference of tumor clonal tree by joint analysis of single-cell SNV and CNA data[J]. BRIEFINGS IN BIOINFORMATICS,2022:12. |
APA | Chen, Ziwei,Gong, Fuzhou,Wan, Lin,&Ma, Liang.(2022).BiTSC2: Bayesian inference of tumor clonal tree by joint analysis of single-cell SNV and CNA data.BRIEFINGS IN BIOINFORMATICS,12. |
MLA | Chen, Ziwei,et al."BiTSC2: Bayesian inference of tumor clonal tree by joint analysis of single-cell SNV and CNA data".BRIEFINGS IN BIOINFORMATICS (2022):12. |
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