Accucopy: accurate and fast inference of allele-specific copy number alterations from low-coverage low-purity tumor sequencing data | |
Fan, Xinping1,2; Luo, Guanghao3; Huang, Yu S.1,2 | |
刊名 | BMC BIOINFORMATICS |
2021-12-15 | |
卷号 | 22期号:1页码:18 |
关键词 | Cancer genomics Copy number alterations Next-generation sequencing |
ISSN号 | 1471-2105 |
DOI | 10.1186/s12859-020-03924-5 |
通讯作者 | Huang, Yu S.(polyactis@gmail.com) |
英文摘要 | Background: Copy number alterations (CNAs), due to their large impact on the genome, have been an important contributing factor to oncogenesis and metastasis. Detecting genomic alterations from the shallow-sequencing data of a low-purity tumor sample remains a challenging task. Results: We introduce Accucopy, a method to infer total copy numbers (TCNs) and allele-specific copy numbers (ASCNs) from challenging low-purity and low-coverage tumor samples. Accucopy adopts many robust statistical techniques such as kernel smoothing of coverage differentiation information to discern signals from noise and combines ideas from time-series analysis and the signal-processing field to derive a range of estimates for the period in a histogram of coverage differentiation information. Statistical learning models such as the tiered Gaussian mixture model, the expectation-maximization algorithm, and sparse Bayesian learning were customized and built into the model. Accucopy is implemented in C++ /Rust, packaged in a docker image, and supports non-human samples, more at http://www.yfish.org/software/. Conclusions: We describe Accucopy, a method that can predict both TCNs and ASCNs from low-coverage low-purity tumor sequencing data. Through comparative analyses in both simulated and real-sequencing samples, we demonstrate that Accucopy is more accurate than Sclust, ABSOLUTE, and Sequenza. |
资助项目 | Chinese Academy of Sciences Hundred-Talent program ; Shanghai Institute of Materia Medica Hundred-Talent program[Y5G6019018] ; Personalized Medicines-Molecular Signature-based Drug Discovery and Development Strategic Priority Research Program of the Chinese Academy of Sciences[XDA12050202] ; State Key Laboratory of Drug Research of Shanghai Institute of Materia Medica[Y5G203F018] |
WOS研究方向 | Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology |
语种 | 英语 |
出版者 | BMC |
WOS记录号 | WOS:000608059100001 |
内容类型 | 期刊论文 |
源URL | [http://119.78.100.183/handle/2S10ELR8/296089] |
专题 | 中国科学院上海药物研究所 |
通讯作者 | Huang, Yu S. |
作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Shanghai Inst Mat Med, State Key Lab Drug Res, Drug Discovery & Design Ctr, Shanghai 201203, Peoples R China 3.Jilin Univ, Sch Pharmaceut Sci, Changchun 130021, Peoples R China |
推荐引用方式 GB/T 7714 | Fan, Xinping,Luo, Guanghao,Huang, Yu S.. Accucopy: accurate and fast inference of allele-specific copy number alterations from low-coverage low-purity tumor sequencing data[J]. BMC BIOINFORMATICS,2021,22(1):18. |
APA | Fan, Xinping,Luo, Guanghao,&Huang, Yu S..(2021).Accucopy: accurate and fast inference of allele-specific copy number alterations from low-coverage low-purity tumor sequencing data.BMC BIOINFORMATICS,22(1),18. |
MLA | Fan, Xinping,et al."Accucopy: accurate and fast inference of allele-specific copy number alterations from low-coverage low-purity tumor sequencing data".BMC BIOINFORMATICS 22.1(2021):18. |
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