To avoid that a pathway is only significant due to a small number of significant SNPs, we performed the multistage integrative pathway (MIP) analysis pipeline four times with different constraints. In
Machine Learning models have been frequently used in transcriptome analyses. Particularly, Representation Learning (RL), e.g., autoencoders, are effective in learning critical representations in noisy
To avoid that a pathway is only significant due to a small number of significant SNPs, we performed the multistage integrative pathway (MIP) analysis pipeline four times with different constraints. In
Total number of genes in each pathway is presented on the diagonal, percentages of overlap are presented in top right half, and number of genes shared is presented in bottom left half.
