Na Cai

Comparative spatial transcriptomics usually partitions tissue into anatomical regions or clusters first and then tests differential expression inside those fixed units, separating localization from testing. SpaceDX instead learns gene-specific spatial attention weights while testing, aggregating spots into an attention-weighted pseudobulk that enters a hierarchical Bayesian logistic regression for subject-level association. In 19 stressed and 19 control mice it found 175 DE genes at 5% empirical FDR, 45.8% more than regional DESeq2's 120; in an Alzheimer's model the two found similar numbers alone, and combining them raised discovery 19.1% over DESeq2 alone.

Comparative spatial transcriptomics usually partitions tissue into anatomical regions or clusters first and then tests differential expression inside those fixed units, separating localization from testing. SpaceDX instead learns gene-specific spatial attention weights while testing, aggregating spots into an attention-weighted pseudobulk that enters a hierarchical Bayesian logistic regression for subject-level association. In 19 stressed and 19 control mice it found 175 DE genes at 5% empirical FDR, 45.8% more than regional DESeq2's 120; in an Alzheimer's model the two found similar numbers alone, and combining them raised discovery 19.1% over DESeq2 alone.