Link to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2023.02.08.527623v1?rss=1
Authors: Cai, G., Chen, Y., Gu, X., Zhou, Z.
Abstract:
Spatial transcriptomics enables the depiction of in situ gene expression and could further be applied to infer the mechanism of cell functions. In this study, we present Spanve (Spatial Neighborhood Variably Expressed Genes), a statistic based approach to detect space-dependent expressed genes from spatial transcriptomics data, which has a high computation efficiency and accuracy by modeling the dependence of space and expression as a distance of two distributions. We demonstrate that Spanve is capable of imputating the spatial transcriptome and improving the identification of spatial tissue regions.
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