Spatial transcriptomics

Mitigation of Multi-scale Biases in Cell-type Deconvolution for Spatially Resolved Transcriptomics Using HarmoDecon
A semi-supervised deep learning model for spatial cell-type deconvolution that mitigates multi-scale biases in spatially resolved transcriptomics.
Zirui Wang, Ke Xu, Yang Liu, Yu Xu 许煜, Lu Zhang
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stDyer enables spatial domain clustering with dynamic graph embedding
An end-to-end deep learning framework for spatial domain clustering in spatially resolved transcriptomics data using dynamic graph embedding and Gaussian Mixture Variational AutoEncoder.
Ke Xu, Yu Xu 许煜, Zirui Wang, Xin Maizie Zhou, Lu Zhang
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stDyer enables spatial domain clustering with dynamic graph embedding