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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
Source PublicationBRIEFINGS IN BIOINFORMATICS
ISSN1467-5463
Pages12
AbstractThe 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.
Keywordsingle-cell DNA sequencing intra-tumor heterogeneity single nucleotide variation copy number alteration Bayesian modeling cancer evolution
DOI10.1093/bib/bbac092
Indexed BySCI
Language英语
Funding ProjectNational 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 Research AreaBiochemistry & Molecular Biology ; Mathematical & Computational Biology
WOS SubjectBiochemical Research Methods ; Mathematical & Computational Biology
WOS IDWOS:000785832000001
PublisherOXFORD UNIV PRESS
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/60305
Collection应用数学研究所
Corresponding AuthorWan, Lin; Ma, Liang
Affiliation1.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
Recommended Citation
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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