单细胞RNA-seq数据缺失元素补全算法  

Algorithm for Missing Elements Completion on Single Cell RNA-seq Data

作　　者：崔璐[1] 刘桂锋[2] CUI Lu;LIU Guifeng(Department of Medical Insurance,China-Japan Union Hospital of Jilin University,Changchun 130033,China;Department of Radiology,China-Japan Union Hospital of Jilin University,Changchun 130033,China)

机构地区：[1]吉林大学中日联谊医院医疗保险管理部,长春130033 [2]吉林大学中日联谊医院放射线科,长春130033

出　　处：《吉林大学学报（理学版）》2020年第5期1229-1231,共3页Journal of Jilin University:Science Edition

基　　金：国家自然科学基金(批准号:21475126,80151459);吉林省科技发展计划项目(批准号:20190701052GH);吴阶平医学基金会项目(批准号:32067501908940).

摘　　要：基于非负矩阵分解模型,提出一种新的数据补全算法.该算法通过循环遍历确定最佳构造矩阵和rank值,解决了单细胞转录组测序(RNA-seq)数据中存在缺失值的问题,避免了由于单细胞测序深度不足对细胞分型分析的影响.在慢性粒细胞白血病单细胞测序数据上的实验结果表明,由补全算法恢复缺失值后的细胞分型更清晰,验证了该算法的有效性.We proposed a novel data completion algorithm based on the nonnegative matrix factorization model.Using the iterative traversal,the algorithm determined the best construction matrix and rank value,which solved the problem of missing value in single cell transcriptome sequencing data(RNA-seq),and avoided the influence of deficiency of the single cell sequencing depth on cell typing analysis.The experimental result on chronic myeloid leukemia data shows that after the missing values are recovered by the completion algorithm,the cell typing is more clear,which verifies the effectiveness of the proposed algorithm.

关 键 词：单细胞RNA-seq数据 缺失元素 非负矩阵分解 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]