GBX1

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

Across TCGA cell cohorts, GBX1 RNA expression is significantly associated with the go_rna of many other GO terms, with 1,189 significant associations in total. SOFT_TISSUE shows the largest number of these associations.

The most reproducible GBX1-associated GO terms across cancer lineages are Cell cycle G1/S phase transition, Regulation of termination of RNA polymerase II transcription, and Regulation of termination of DNA-templated transcription. Each is linked with GBX1 in more than 5 cancer types. Because this analysis shows association rather than direction, both GBX1-to-partner and partner-to-GBX1 results are reported.

Each partner links to its own Q-omics profile. The box plot shows the strongest example, Cell cycle G1/S phase transition grouped by GBX1-low versus GBX1-high in SOFT_TISSUE.

RNA expression associated GO terms by consensus

Ranked by combined sampling and lineage consensus. X-score (GBX1→partner) and Y-score (partner→GBX1) 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
SOFT_TISSUECell cycle G1/S phase transition →+0.075+0.337<.001.00436
SOFT_TISSUERegulation of termination of RNA polymerase II transcription →+0.090+0.346<.001.00336
SOFT_TISSUERegulation of termination of DNA-templated transcription →+0.090+0.346<.001.00336
SOFT_TISSUERegulation of sister chromatid cohesion →+0.151+0.629<.001.00335
SOFT_TISSUEMicrotubule cytoskeleton organization involved in mitosis →+0.062+0.320.001.00635
OVARYRegulation of termination of RNA polymerase II transcription, poly(A)-coupled →+0.092+0.064.002.00826
Each partner links to its Q-omics profile. Showing the 6 strongest of 1,189 associations by consensus.

Cell cycle G1/S phase transition by GBX1 expression — SOFT_TISSUE

Box plot of Cell cycle G1/S phase transition in GBX1-low vs GBX1-high samples in SOFT_TISSUE.

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Exploration