MaizeNet can stratify candidate genes from unbiased forward-genetics such as GWAS via associations with subnetworks enriched for relevant GOBP annotations.
For this purpose, we generated subnetworks of MaizeNet through overlapping Markov clustering (Shih and Parthasarathy, 2012),
and measured enrichment of GWAS candidate genes across 2335 MaizeNet subnetworks containing at least 5 genes.
GWAS candidates generally contain many false positives.
If significantly associated subnetworks with the given GWAS candidate genes (# overlap genes ≥ 2 and P < 0.01) are also enriched for relevant GOBP annotations,
the subnetwork is likely to be a functional module for the trait and the associated candidate genes are more likely to be involved in the trait.