计算生物学
计算机科学
RNA序列
破骨细胞
数据挖掘
生物
遗传学
基因
基因表达
转录组
体外
作者
H. Okada,Ung‐il Chung,Hironori Hojo
标识
DOI:10.1007/s11914-023-00840-4
摘要
This review paper provides step-by-step instructions on the fundamental process, from handling fastq datasets to illustrating plots and drawing trajectories.The number of studies using single-cell RNA-seq (scRNA-seq) is increasing. scRNA-seq revealed the heterogeneity or diversity of the cellular populations. scRNA-seq also provides insight into the interactions between different cell types. User-friendly scRNA-seq packages for ligand-receptor interactions and trajectory analyses are available. In skeletal biology, osteoclast differentiation, fracture healing, ectopic ossification, human bone development, and the bone marrow niche have been examined using scRNA-seq. scRNA-seq data analysis tools are still being developed, even at the fundamental step of dataset integration. However, updating the latest information is difficult for many researchers. Investigators and reviewers must share their knowledge of in silico scRNA-seq for better biological interpretation. This review article aims to provide a useful guide for complex analytical processes in single-cell RNA-seq data analysis.
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