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
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