计算生物学
核糖核酸
RNA序列
转录组
生物
仿形(计算机编程)
基因表达谱
鉴定(生物学)
基因表达
基因
计算机科学
遗传学
植物
操作系统
作者
Doyoung Kim,Kyung Bae Chung,Tae Kyun Kim
标识
DOI:10.1016/j.jdermsci.2020.06.002
摘要
The bulk tissue RNA sequencing technique measures the average gene expression of potentially heterogeneous cellular subsets of human skin. However, single-cell RNA sequencing (scRNA-seq) enables both profiling of gene expression measurements at a single-cell resolution and identification of cellular heterogeneity. This recent technical advance has broadened the understanding of many aspects of skin biology, such as development, oncogenesis, and immunopathogenesis. However, due to the low number of mRNAs detectable in an individual cell and the alteration of transcriptomes during sample preparation, scRNA-seq data are often extremely noisy. Moreover, unstandardized methodologies for sample preparation, capturing, and bioinformatic analysis (e.g., batch correction or integration) hamper reliable inter-study comparisons. Nevertheless, sophisticated bioinformatic analysis and integrative omics-based approaches are making up for these limitations. Here, we discuss both the advantages and technical challenges of scRNA-seq, a promising tool opening new horizons in dermatological research.
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