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BiTSC2: Bayesian inference of tumor clonal tree by joint analysis of single-cell SNV and CNA data

文献类型：期刊论文

作者Chen, Ziwei2; Gong, Fuzhou1,3; Wan, Lin1,3; Ma, Liang4
刊名BRIEFINGS IN BIOINFORMATICS
出版日期2022-04-02
页码12
ISSN号1467-5463
关键词single-cell DNA sequencing intra-tumor heterogeneity single nucleotide variation copy number alteration Bayesian modeling cancer evolution
DOI10.1093/bib/bbac092
英文摘要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.
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
语种英语
出版者OXFORD UNIV PRESS
WOS记录号WOS:000785832000001
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/60304]  
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.Univ Chinese Acad Sci, Sch Math Sci, Beijing, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
3.Chinese Acad Sci, Acad Math & Syst Sci, Natl Ctr Math & Interdisciplinary Sci, Beijing 100190, Peoples R China
4.Chinese Acad Sci, Inst Zool, Key Lab Zool Systemat & Evolut, Beijing 100101, 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.

入库方式： OAI收割

来源：数学与系统科学研究院

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