scRNA‐seq data analysis method to improve analysis performance

Autor: Junru Lu, Yuqi Sheng, Weiheng Qian, Min Pan, Xiangwei Zhao, Qinyu Ge
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: IET Nanobiotechnology, Vol 17, Iss 3, Pp 246-256 (2023)
Druh dokumentu: article
ISSN: 1751-875X
1751-8741
DOI: 10.1049/nbt2.12115
Popis: Abstract With the development of single‐cell RNA sequencing technology (scRNA‐seq), we have the ability to study biological questions at the level of the individual cell transcriptome. Nowadays, many analysis tools, specifically suitable for single‐cell RNA sequencing data, have been developed. In this review, the currently commonly used scRNA‐seq protocols are discussed. The upstream processing flow pipeline of scRNA‐seq data, including goals and popular tools for reads mapping and expression quantification, quality control, normalization, imputation, and batch effect removal is also introduced. Finally, methods to evaluate these tools in both cellular and genetic dimensions, clustering and differential expression analysis are presented.
Databáze: Directory of Open Access Journals
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