UFM1

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

Across TCGA cell cohorts, UFM1 RNA expression is significantly associated with the go_rna of many other GO terms, with 2,233 significant associations in total. BLOOD_Lymphoma shows the largest number of these associations.

The most reproducible UFM1-associated GO terms across cancer lineages are Negative regulation of hematopoietic stem cell differentiation, Retrograde transport, vesicle recycling within Golgi, and Protein polyufmylation. Each is linked with UFM1 in more than 17 cancer types. Because this analysis shows association rather than direction, both UFM1-to-partner and partner-to-UFM1 results are reported.

Each partner links to its own Q-omics profile. The box plot shows the strongest example, Negative regulation of hematopoietic stem cell differentiation grouped by UFM1-low versus UFM1-high in LUNG_SCLC.

RNA expression associated GO terms by consensus

Ranked by combined sampling and lineage consensus. X-score (UFM1→partner) and Y-score (partner→UFM1) 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_SCLCNegative regulation of hematopoietic stem cell differentiation →+0.173+0.943<.001.001318
PANCREASRetrograde transport, vesicle recycling within Golgi →+0.148+1.073<.001<.001317
BLOOD_MyelomaProtein polyufmylation →+0.145+0.867.003.008315
BLOOD_MyelomaProtein K69-linked ufmylation →+0.145+0.867.003.008315
BLOOD_MyelomaProtein ufmylation →+0.146+1.044<.001<.001315
OESOPHAGUSIntra-Golgi vesicle-mediated transport →+0.089+0.767.001<.001313
Each partner links to its Q-omics profile. Showing the 6 strongest of 2,233 associations by consensus.

Negative regulation of hematopoietic stem cell differentiation by UFM1 expression — LUNG_SCLC

Box plot of Negative regulation of hematopoietic stem cell differentiation in UFM1-low vs UFM1-high samples in LUNG_SCLC.

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Exploration