可视化
计算机科学
数据可视化
计算生物学
转录组
交互式可视化
人工智能
数据挖掘
探索性数据分析
基因组学
模式识别(心理学)
RNA序列
基因表达谱
空间分析
作者
Boxiang Liu,Yanjun Li,Liang Zhang
标识
DOI:10.3389/fgene.2021.785290
摘要
Human and animal tissues consist of heterogeneous cell types that organize and interact in highly structured manners. Bulk and single-cell sequencing technologies remove cells from their original microenvironments, resulting in a loss of spatial information. Spatial transcriptomics is a recent technological innovation that measures transcriptomic information while preserving spatial information. Spatial transcriptomic data can be generated in several ways. RNA molecules are measured by in situ sequencing, in situ hybridization, or spatial barcoding to recover original spatial coordinates. The inclusion of spatial information expands the range of possibilities for analysis and visualization, and spurred the development of numerous novel methods. In this review, we summarize the core concepts of spatial genomics technology and provide a comprehensive review of current analysis and visualization methods for spatial transcriptomics.
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