Missing Value Imputation With Low-Rank Matrix Completion in Single-Cell RNA-Seq Data by Considering Cell Heterogeneity

Missing Value Imputation With Low-Rank Matrix Completion in Single-Cell RNA-Seq Data by Considering Cell Heterogeneity

Single-cell RNA-sequencing (scRNA-seq) technologies enable the measurements of gene expressions in individual cells, which is helpful for exploring cancer heterogeneity and precision medicine. However, various technical noises lead to false zero values (missing gene expression values) in scRNA-seq d...

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Bibliographic Details
Main Authors: Meng Huang, Xiucai Ye, Hongmin Li, Tetsuya Sakurai
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-07-01
Series:Frontiers in Genetics
Subjects:
single-cell RNA-seq
dropout
imputation
low-rank matrix completion
precision medicine
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2022.952649/full

Internet

https://www.frontiersin.org/articles/10.3389/fgene.2022.952649/full

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