YAP and TAZ Dictate Binary Pan-Cancer Superclasses [RNA-seq]
We defined pan-cancer binary classes based on distinct expression of YAP (and its paralog TAZ/ WWTR1) and YAP-responsive adhesion regulators. Combining informatics with in vivo and in vitro gain- and loss-of-function studies across multiple murine and human tumor types, we showed that opposite pro- or anti-cancer YAP activity functionally defines binary YAPon or YAPoff cancer classes that express or silence YAP, respectively. Essentially all leukemia and lymphoma fall into the YAPoff class, as d...
Provenance — who produced it, who reused it
Linked to 1 papers in the literature. Roles are inferred factual signals (who deposited the data vs who reused it), with counts — never a judgement about any author.
Deep data QC
100/100 · AStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
This human RNA-Seq with unavailable details shows good quality (94.8% Q30) and mean read length of 100.1 bp. Missing metadata limits characterization.
The A grade is a transparent weighted average. Each metric below scored from 0–100% against the published bulk-RNA-seq thresholds, weighted by its importance; nothing is hidden or subjective.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0