SCC: an accurate imputation method for scRNA-seq dropouts based on a mixture model

SCC: an accurate imputation method for scRNA-seq dropouts based on a mixture model

Background: Single-cell RNA sequencing (scRNA-seq) enables the possibility of many in-depth transcriptomic analyses at a single-cell resolution. It’s already widely used for exploring the dynamic development process of life, studying the gene regulation mechanism, and discovering new cell types. How...

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Bibliographic Details
Main Authors:	Hu, J. (Author), Shang, X. (Author), Zheng, Y. (Author), Zhong, Y. (Author)
Format:	Article
Language:	English
Published:	BioMed Central Ltd 2021
Subjects:	article biological model Cells Clustering accuracy Cytology Dropouts identification Dynamic development Effective tool Gene expression estimation gene expression profiling Gene Expression Profiling gene expression regulation Gene Expression Regulation Gene regulation mechanism genetics genomics Genomics Imputation methods Mixture model Models, Genetic noise Noise procedures RNA Rna sequencing RNA, Small Cytoplasmic ScRNA-seq simulation single cell analysis Single cell resolution single cell RNA seq Single-Cell Analysis small cytoplasmic RNA
Online Access:	View Fulltext in Publisher

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