A review of recent advances in spatially resolved transcriptomics data analysis

被引:0
|
作者
Gao, Yue [1 ]
Gao, Ying-Lian [2 ]
Jing, Jing [1 ]
Li, Feng [1 ]
Zheng, Chun-Hou [3 ]
Liu, Jin-Xing [4 ]
机构
[1] Qufu Normal Univ, Sch Comp Sci, Rizhao 276826, Peoples R China
[2] Qufu Normal Univ, Qufu Normal Univ Lib, Rizhao 276826, Peoples R China
[3] Qufu Normal Univ, Sch Software Engn, Qufu 273165, Peoples R China
[4] Univ Hlth & Rehabil Sci, Sch Hlth & Life Sci, Qingdao 266113, Peoples R China
基金
中国国家自然科学基金;
关键词
Spatially resolved transcriptomics; Spatial clustering; Spatial trajectory inference; Batch effect correction; Gene expression denoising; CELL; EXPRESSION; IDENTIFICATION;
D O I
10.1016/j.neucom.2024.128283
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The increasing significance of spatial organization and our understanding of molecular characteristics have greatly contributed to technological advancements in spatially resolved transcriptomics (SRT). Its development provides a new perspective to explore the spatial specificity of gene expression, which assists in revealing the interactions between tissues and cells, along with abnormal gene expression patterns in disease development, further enhancing our comprehension of gene regulation mechanisms in organisms. The main purpose of this review is to introduce some of the latest developments in the analysis and development of spatial transcriptomics data, and emphasize their current research approaches in spatial clustering, spatial trajectory inference, identification of spatially variable genes, cell-cell/gene-gene interaction, batch effect correction and gene expression denoising.
引用
收藏
页数:18
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