Data normalization for addressing the challenges in the analysis of single-cell transcriptomic datasets

Background Normalization is a critical step in the analysis of single-cell RNA-sequencing (scRNA-seq) datasets. Its main goal is to make gene counts comparable within and between cells. To do so, normalization methods must account for technical and biological variability. Numerous normalization meth...

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Vydané v:	BMC genomics Ročník 25; číslo 1; s. 444 - 18
Hlavní autori:	Cuevas-Diaz Duran, Raquel, Wei, Haichao, Wu, Jiaqian
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London BioMed Central 06.05.2024 BioMed Central Ltd Springer Nature B.V BMC
Predmet:	Algorithms Analysis Animal Genetics and Genomics Animals Automation Bar codes Biological variability Biomedical and Life Sciences Cells Data analysis Datasets Decision making Gene expression Gene Expression Profiling - methods Gene Expression Profiling - standards Gene sequencing Genes Genetic research Genomics Humans Impact analysis Information management Life Sciences Machine learning Mathematical models Methods Microarrays Microbial Genetics and Genomics Normalization Performance assessment Performance evaluation Plant Genetics and Genomics Proteomics Reagents Review RNA RNA sequencing RNA-Seq - methods RNA-Seq - standards scRNA-seq Sequence Analysis, RNA - methods Single-Cell Analysis - methods Single-cell sequencing Statistical models Technical variability Transcriptome Transcriptomics Variability Canada Mexico Single-cell sequencing scRNA-seq Normalization Technical variability Biological variability
ISSN:	1471-2164, 1471-2164
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