GIP

RNA expression — cross-omics
Cross-omicsRNA → FUNCTION-RNACell-linePairwise association · TCGA cohorts

Across TCGA cell cohorts, GIP RNA expression is significantly associated with the go_rna of many other GO terms, with 876 significant associations in total. BONE shows the largest number of these associations.

The most reproducible GIP-associated GO terms across cancer lineages are Alpha-beta T cell activation involved in immune response, T cell differentiation involved in immune response, and Regulation of intestinal cholesterol absorption. Each is linked with GIP in more than 3 cancer types. Because this analysis shows association rather than direction, both GIP-to-partner and partner-to-GIP results are reported.

Each partner links to its own Q-omics profile. The box plot shows the strongest example, Alpha-beta T cell activation involved in immune response grouped by GIP-low versus GIP-high in LUNG_NSCLC_LUAD.

RNA expression associated GO terms by consensus

Ranked by combined sampling and lineage consensus. X-score (GIP→partner) and Y-score (partner→GIP) are standardized regression coefficients; both directions are reported because the association is undirected. p-values are from the association test.
LineagePartner GO termX-scoreY-scorep(X)p(Y)Sampling consensusLineage consensus
LUNG_NSCLC_LUADAlpha-beta T cell activation involved in immune response →+0.078+0.244<.001.00734
LUNG_NSCLC_LUADT cell differentiation involved in immune response →+0.078+0.244<.001.00734
LUNG_NSCLC_LUADRegulation of intestinal cholesterol absorption →+0.125+0.259.002.00434
LUNG_NSCLC_LUADLinoleic acid metabolic process →+0.144+0.410.001.00134
SKINNegative regulation of cell fate commitment →+0.196+0.035<.001.00334
SKINLactate metabolic process →+0.064+0.029.002.00934
Each partner links to its Q-omics profile. Showing the 6 strongest of 876 associations by consensus.

Alpha-beta T cell activation involved in immune response by GIP expression — LUNG_NSCLC_LUAD

Box plot of Alpha-beta T cell activation involved in immune response in GIP-low vs GIP-high samples in LUNG_NSCLC_LUAD.

Explore this box plot interactively →

Exploration