Deciphering spatial domains from spatially resolved transcriptomics with Siamese graph autoencoder.

Lei CaoChao YangLuni HuWenjian JiangYating RenTianyi XiaMengyang XuYishuai JiMei LiXue Liu Yuxiang Li Yong Zhang Shuangsang Fang

Published in: GigaScience (2024)

Benchmarking results from various ST datasets generated by diverse platforms demonstrate compelling evidence for the effectiveness of SGAE against other ST clustering methods. Specifically, SGAE exhibits potential for extension and application on multislice 3D reconstruction and tissue structure investigation. The source code and a collection of spatial clustering results can be accessed at https://github.com/STOmics/SGAE/.

Keyphrases

single cell
rna seq
randomized controlled trial
systematic review
convolutional neural network
magnetic resonance imaging
human health
risk assessment
neural network