Mavatar Curated Gene Lists
Our proprietary network comparison framework identifies both conserved molecular processes and context-specific functional rewiring across networks. This approach yields two complementary outcomes:
- Network Core Genes: genes whose network topology is significantly similar across multiple networks, meaning that their wiring patterns are conserved across tissues and conditions. We hypothesize based on our findings that these represent evolutionarily conserved pathways and modules that maintain consistent connectivity regardless of biological context. Because these genes behave similarly in different contexts, they can dominate network topology and mask the tissue- or condition-specific gene-gene correlations that are often more informative. Using the FilterFilter menu (a button on the right side of Generate Graph ), you can Hide Network Core Genes to remove this conserved signal and focus on the interactions that are unique to your context of interest.
- Network Specific Genes: genes whose network topology within a specific context differs significantly from corresponding networks in other contexts, indicating uniquely altered connectivity patterns. These are Network Derived Signatures: pre-calculated, context-specific, 100% data-driven gene lists that reflect the distinctive wiring of each context and tissue.
These signatures are identified through Module ConstructionModule Construction in combination with iterative subnetwork comparisons performed against all other available networks using the DeltaCon method, which quantifies topological similarity between networks. For more details on how network similarity is assessed, see the DINA Network SimilarityDINA Network Similarity card.
Both the network core genes and the network specific genes are ready for immediate use in Generate GraphGenerate Graph with Mavatar Curated Lists, and in identifying functionally enrichedfunctionally enriched modules. They are additionally found within the HighlightHighlight feature under Mavatar Module, leading to easy identification of conserved/context-specific module-associated genes within the graph. Together, these two outputs let you separate the conserved biology shared across contexts from the distinctive biology specific to your network, ensuring that your downstream analyses focus on the signal most relevant to your research question.