RN7SL727P

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

Across TCGA patient cohorts, RN7SL727P RNA expression is significantly associated with the go_rna of many other GO terms, with 5,655 significant associations in total. STAD shows the largest number of these associations.

The most reproducible RN7SL727P-associated GO terms across cancer lineages are Positive regulation of transmembrane transport, Positive regulation of canonical NF-kappaB signal transduction, and Vesicle-mediated transport in synapse. Each is linked with RN7SL727P in more than 7 cancer types. Because this analysis shows association rather than direction, both RN7SL727P-to-partner and partner-to-RN7SL727P results are reported.

Each partner links to its own Q-omics profile. The box plot shows the strongest example, Positive regulation of transmembrane transport grouped by RN7SL727P-low versus RN7SL727P-high in ESCA.

RNA expression associated GO terms by consensus

Ranked by combined sampling and lineage consensus. X-score (RN7SL727P→partner) and Y-score (partner→RN7SL727P) 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
ESCAPositive regulation of transmembrane transport →+0.079+0.074<.001.00928
ESCAPositive regulation of canonical NF-kappaB signal transduction →+0.201+0.095<.001.00836
ESCAVesicle-mediated transport in synapse →+0.120+0.048<.001.00535
ESCANeuron apoptotic process →+0.166+0.046<.001.00717
ESCAIntrinsic apoptotic signaling pathway by p53 class mediator →+0.209+0.047<.001.00526
ESCAMembrane fusion →+0.151+0.101<.001.00235
Each partner links to its Q-omics profile. Showing the 6 strongest of 5,655 associations by consensus.

Positive regulation of transmembrane transport by RN7SL727P expression — ESCA

Box plot of Positive regulation of transmembrane transport in RN7SL727P-low vs RN7SL727P-high samples in ESCA.

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Exploration