GraphCpG: imputation of single-cell methylomes based on locus-aware neighboring subgraphs

作者全名："Deng, Yuzhong; Tang, Jianxiong; Zhang, Jiyang; Zou, Jianxiao; Zhu, Que; Fan, Shicai"

作者地址："[Deng, Yuzhong; Tang, Jianxiong; Zhang, Jiyang; Zou, Jianxiao; Fan, Shicai] Univ Elect Sci & Technol China, Sch Automat Engn, Chengdu 611731, Sichuan, Peoples R China; [Zou, Jianxiao; Fan, Shicai] Univ Elect Sci & Technol China, Shenzhen Inst Adv Study, Shenzhen 518110, Guangdong, Peoples R China; [Zhu, Que] Chongqing Med Univ, Dept Out Patient, Affiliated Hosp 2, Chongqing 400010, Peoples R China"

通信作者："Fan, SC (通讯作者)，Univ Elect Sci & Technol China, Sch Automat Engn, Chengdu 611731, Sichuan, Peoples R China.; Fan, SC (通讯作者)，Univ Elect Sci & Technol China, Shenzhen Inst Adv Study, Shenzhen 518110, Guangdong, Peoples R China.; Zhu, Q (通讯作者)，Chongqing Med Univ, Dept Out Patient, Affiliated Hosp 2, Chongqing 400010, Peoples R China."

来源：BIOINFORMATICS

ESI学科分类：BIOLOGY & BIOCHEMISTRY

WOS号：WOS:001079181600007

JCR分区：Q1

影响因子：4.4

年份：2023

卷号：39

期号：9

开始页：　

结束页：　

文献类型：Article

关键词：　

摘要："Motivation Single-cell DNA methylation sequencing can assay DNA methylation at single-cell resolution. However, incomplete coverage compromises related downstream analyses, outlining the importance of imputation techniques. With a rising number of cell samples in recent large datasets, scalable and efficient imputation models are critical to addressing the sparsity for genome-wide analyses.Results We proposed a novel graph-based deep learning approach to impute methylation matrices based on locus-aware neighboring subgraphs with locus-aware encoding orienting on one cell type. Merely using the CpGs methylation matrix, the obtained GraphCpG outperforms previous methods on datasets containing more than hundreds of cells and achieves competitive performance on smaller datasets, with subgraphs of predicted sites visualized by retrievable bipartite graphs. Besides better imputation performance with increasing cell number, it significantly reduces computation time and demonstrates improvement in downstream analysis.Availability and implementation The source code is freely available at https://github.com/yuzhong-deng/graphcpg.git."

基金机构：National Natural Science Foundation of China [61872063]; Shenzhen Science and Technology Program [JCYJ20210324140407021]

基金资助正文：This work was supported by the National Natural Science Foundation of China [no. 61872063]; Shenzhen Science and Technology Program [no. JCYJ20210324140407021].