Computational Strategies and Algorithms for Inferring Cellular Composition of Spatial Transcriptomics Data  

作　　者：Xiuying Liu Xianwen Ren 

机构地区：[1]Changping Laboratory,Beijing 102206,China

出　　处：《Genomics, Proteomics & Bioinformatics》2024年第3期1-9,共9页基因组蛋白质组与生物信息学报（英文版）

基　　金：supported by Changping Laboratory,China.Thank Xiangxing Jin for helping prepare the illustrations in this work.

摘　　要：Spatial transcriptomics technology has been an essential and powerful method for delineating tissue architecture at the molecular level.However,due to the limitations of the current spatial techniques,the cellular information cannot be directly measured but instead spatial spots typically varying from a diameter of 0.2 to 100µm are characterized.Therefore,it is vital to apply computational strategies for inferring the cellular composition within each spatial spot.The main objective of this review is to summarize the most recent progresses in estimating the exact cellular proportions for each spatial spot,and to prospect the future directions of this field.

关 键 词：Spatial transcriptomics Single-cell sequencing Cellular composition Spot deconvolution Cell type decomposition 

分 类 号：Q811.4[生物学—生物工程]