Recovering Spatially-Varying Cell-Specific Gene Co-expression Networks for Single-Cell Spatial Expression Data.

ABSTRACT: Recent advances in single-cell technologies enable spatial expression profiling at the cell level, making it possible to elucidate spatial changes of cell-specific genomic features. The gene co-expression network is an important feature that encodes the gene-gene marginal dependence structure and allows for the functional annotation of highly connected genes. In this paper, we design a simple and computationally efficient two-step algorithm to recover spatially-varying cell-specific gene co-expression networks for single-cell spatial expression data. The algorithm first estimates the gene expression covariance matrix for each cell type and then leverages the spatial locations of cells to construct cell-specific networks. The second step uses expression covariance matrices estimated in step

SUBMITTER: Yu J 

PROVIDER: S-EPMC8107398 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature