Related Experiment Video
Updated: Jul 12, 2025
Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
Published on: July 6, 2022
SPIRAL: integrating and aligning spatially resolved transcriptomics data across different experiments, conditions,
Tiantian Guo1,2, Zhiyuan Yuan3, Yan Pan4
1School of Software Engineering, Beijing Jiaotong University, Beijing, 100044, China.
Abstract:
Properly integrating spatially resolved transcriptomics (SRT) generated from different batches into a unified gene-spatial coordinate system could enable the construction of a comprehensive spatial transcriptome atlas. Here, we propose SPIRAL, consisting of two consecutive modules: SPIRAL-integration, with graph domain adaptation-based data integration, and SPIRAL-alignment, with cluster-aware optimal transport-based coordination alignment. We verify SPIRAL with both synthetic and real SRT datasets. By encoding spatial correlations to gene expressions, SPIRAL-integration surpasses state-of-the-art methods in both batch effect removal and joint spatial domain identification. By aligning spots cluster-wise, SPIRAL-alignment achieves more accurate coordinate alignments than existing methods.
More Related Videos
12:54Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
Published on: March 7, 2018
10:41Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms
Published on: May 9, 2017
