Matched Interaction Across Tissues (MIxT)
The Matched Interaction Across Tissues (MIxT) is a system designed for exploring and comparing transcriptional profiles from two or more matched tissues across individuals. Here, the MIxT system is applied to tumor and blood transcriptional profiles from breast cancer patients from the Norwegian Women and Cancer study.
In a network, genes can be represented by nodes colored by their module membership. A pair of nodes is connected with an edge if there is a significant co-expresson relationship between them (topological overlap > 0.1). In both tissues, the edges that span between modules reflect natural overlaps between cellular processes enriched in modules.
To explore the system-level changes across tumor and the systemic response of patients, we constructed tight coexpression gene sets (also called modules) in tumor and blood tissue, respectively. MIxT enables the exploration of module content, expression profiles, and functional enrichment. Visualizes how module expression orders patients to identify clinicopathological variables associated with each module. Allows to explore blood module expression in breast cancer patients compared to healthy controls.
Displays significance of gene overlap between modules across tissues as such an overlap may suggest a very simple “mirrored” type of co-expression patterns. Visualizes expression of genes in common between modules across tissues. Displays significance of interactions between modules defined by the correlation between patient orderings induced by modules. Allows selection of a particular subtype. Visualizes expression of genes in modules interacting between tissues across all patients or within a subtype of interest.
Link to Clinical Variables
Displays significance of associations between module expression and clinical variables. Allows selection of a particular subtype and exploration of module expression profiles of interest.
Submit your own gene list
Given a gene list of interest, return modules in which the gene list is enriched for.
Search for a gene or pathway and return modules in which the gene or pathway is present or enriched. Investigate which genes are co-expressed with your gene of interest in blood and tumor from breast cancer patients.