SpaGE: Spatial Gene Enhancement using scRNA-seq

Abstract: Single-cell technologies are emerging fast due to their ability to unravel the heterogeneity of biological systems. While scRNA-seq is a powerful tool that measures whole-transcriptome expression of single cells, it lacks their spatial localization. Novel spatial transcriptomics methods do retain cells spatial information but can only measure tens to hundreds of transcripts. To resolve this discrepancy, we developed SpaGE, a method that integrates spatial and scRNA-seq datasets to predict whole-transcriptome expressions in their spatial configuration. Using five dataset-pairs, SpaGE outperformed previously published methods and showed scalability to large datasets. Moreover, SpaGE predicted new spatial gene patterns that are confirmed independently.

Tamim Abdelaal, Soufiane Mourragui, Ahmed Mahfouz, and Marcel Reinders. SpaGE: Spatial Gene Enhancement using scRNA-seq. BioRxiv, 2020.
@article { bib:2020_spage_preprint,
author = { Tamim Abdelaal and Soufiane Mourragui and Ahmed Mahfouz and Marcel Reinders },
title = { SpaGE: Spatial Gene Enhancement using scRNA-seq },
year = { 2020 },
SpaGE screenshot