Detection of differentially expressed genes in spatial transcriptomics data by spatial analysis of spatial transcriptomics: A novel method based on spatial statistics

Spatial transcriptomics (STs) simultaneously obtains the location and amount of gene expression within a tissue section. However, current methods like FindMarkers calculated the differentially expressed genes (DEGs) based on the classical statistics, which should abolish the spatial information. A n...

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Published inFrontiers in neuroscience Vol. 16; p. 1086168
Main Authors Qiu, Zhihua, Li, Shaojun, Luo, Ming, Zhu, Shuanggen, Wang, Zhijian, Jiang, Yongjun
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 29.11.2022
Subjects
DEGs
Neuroscience
saSpatial
spatial statistics
spatial transcriptomics
stroke
DEGs
spatial statistics
stroke
spatial transcriptomics
saSpatial
Online AccessGet full text
ISSN1662-453X
1662-4548
1662-453X
DOI10.3389/fnins.2022.1086168

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Summary:Spatial transcriptomics (STs) simultaneously obtains the location and amount of gene expression within a tissue section. However, current methods like FindMarkers calculated the differentially expressed genes (DEGs) based on the classical statistics, which should abolish the spatial information. A new method named spatial analysis of spatial transcriptomics (saSpatial) was developed for both the location and the amount of gene expression. Then saSpatial was applied to detect DEGs in both inter- and intra-cross sections. DEGs detected by saSpatial were compared with those detected by FindMarkers. Spatial analysis of spatial transcriptomics was founded on the basis of spatial statistics. It was able to detect DEGs in different regions in the normal brain section. As for the brain with ischemic stroke, saSpatial revealed the DEGs for the ischemic core and penumbra. In addition, saSpatial characterized the genetic heterogeneity in the normal and ischemic cortex. Compared to FindMarkers, a larger number of valuable DEGs were found by saSpatial. Spatial analysis of spatial transcriptomics was able to effectively detect DEGs in STs data. It was a simple and valuable tool that could help potential researchers to find more valuable genes in the future research.
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Edited by: Yuwen Li, Sichuan University, China
Reviewed by: Fang Wang, Nanjing General Hospital of Nanjing Military Command, China; Dezhi Liu, Shanghai University of Traditional Chinese Medicine, China; Xiaomeng Xu, Shanghai Jiao Tong University, China
These authors have contributed equally to this work
This article was submitted to Translational Neuroscience, a section of the journal Frontiers in Neuroscience
ISSN:1662-453X
1662-4548
1662-453X
DOI:10.3389/fnins.2022.1086168