生物
限制
工作流程
背景(考古学)
转录组
计算生物学
核糖核酸
空间语境意识
遗传学
数据科学
基因
基因表达
人工智能
工程类
计算机科学
机械工程
古生物学
数据库
作者
Kelvin Adema,Michael A. Schon,Michael D. Nodine,Wouter Kohlen
标识
DOI:10.1016/j.tplants.2024.03.010
摘要
Plant scientists are rapidly integrating single-cell RNA sequencing (scRNA-seq) into their workflows. Maximizing the potential of scRNA-seq requires a proper understanding of the spatiotemporal context of cells. However, positional information is inherently lost during scRNA-seq, limiting its potential to characterize complex biological systems. In this review we highlight how current single-cell analysis pipelines cannot completely recover spatial information, which confounds biological interpretation. Various strategies exist to identify the location of RNA, from classical RNA in situ hybridization to spatial transcriptomics. Herein we discuss the possibility of utilizing this spatial information to supervise single-cell analyses. An integrative approach will maximize the potential of each technology, and lead to insights which go beyond the capability of each individual technology.
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