Characterisation of COMPASS activity in ageing yeast
Here we analyse steady mRNA levels in wild type and COMPASS mutants across an ageing timecourse, along with H3K4me3 distribution in ageing wild type
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
95/100 · AStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
Bulk RNA-seq of Saccharomyces cerevisiae with unavailable platform information (HTTP error), but exceptional quality metrics (98.3% Q30, 51 bp read length, 0.001% N content). This dataset captures yeast transcriptomics with minimal contamination. The short-read length and exceptional quality suggest optimized library preparation for efficient multiplex sequencing in this model organism.
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