PSME1

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

Across TCGA cell cohorts, PSME1 RNA expression is significantly associated with the go_rna of many other GO terms, with 4,287 significant associations in total. BLOOD_Leukemia shows the largest number of these associations.

The most reproducible PSME1-associated GO terms across cancer lineages are Negative regulation of viral genome replication, CD8-positive, alpha-beta T cell homeostasis, and Negative regulation of viral process. Each is linked with PSME1 in more than 13 cancer types. Because this analysis shows association rather than direction, both PSME1-to-partner and partner-to-PSME1 results are reported.

Each partner links to its own Q-omics profile. The box plot shows the strongest example, Negative regulation of viral genome replication grouped by PSME1-low versus PSME1-high in SOFT_TISSUE.

RNA expression associated GO terms by consensus

Ranked by combined sampling and lineage consensus. X-score (PSME1→partner) and Y-score (partner→PSME1) 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_TISSUENegative regulation of viral genome replication →+0.165+1.200<.001<.001314
URINARY_TRACTCD8-positive, alpha-beta T cell homeostasis →+0.156+0.895.003.001313
SOFT_TISSUENegative regulation of viral process →+0.135+1.301<.001<.001313
URINARY_TRACTNegative regulation of regulatory T cell differentiation →+0.211+0.971.002.004313
PANCREASNegative regulation of response to biotic stimulus →+0.080+0.758.001<.001312
PANCREASPositive regulation of chromatin binding →+0.255+0.973<.001<.001311
Each partner links to its Q-omics profile. Showing the 6 strongest of 4,287 associations by consensus.

Negative regulation of viral genome replication by PSME1 expression — SOFT_TISSUE

Box plot of Negative regulation of viral genome replication in PSME1-low vs PSME1-high samples in SOFT_TISSUE.

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