Fig. 3
From: PheSeq, a Bayesian deep learning model to enhance and interpret the gene-disease association studies
View of data congruence in three case studies. a 3-D semantic representation of AD genes; b BC genes with 3-D representation; c LC genes with 3-D representation. With the color gradient representing the significance level by a single sequence analysis, genes after the phenotypic embedding computation are projected onto a 3-D semantic space. Intuitively, the significant and less significant disease-associated genes are distinguished along the manifold direction based on their phenotypic embeddings. The observation suggests the high data quality of association significance and phenotype description, which supports the subsequent data fusion