1. ADAGE model example.
ADAGE model example. For one sample in the expression compendium (one column in the figure with red or green colors, representing expression values of various genes), random noise is first added to the expression value. The corrupted expression values are then encoded into 50 nodes through a gene-to-node weight matrix, which connects each gene to each node. A red solid line represents a high-weight relationship between a gene and a node, indicating that the gene has a stronger influence on the node’s activity than other genes (connected by black dotted lines). Node activities derived from this sample are decoded back into reconstructed expression values through the same weight matrix. Samples in the compendium are trained through the encoding and decoding steps with the goal of minimizing differences between initial expression values and reconstructed expression values. The resulting ADAGE model constructs nodes from genomic measurements that can be interpreted as biologically meaningful features, such as genome divergence among strains and transcriptional responses to oxygen abundance.
Jie Tan et al. mSystems 2016; doi: /mSystems