Longitudinal tracking of whole blood gene-expression in healthy young and old individuals - 2015
Immune responses generally decline with age. We used multiple ‘omics’ technologies to capture population- and individual- level changes in the human immune system of 135 healthy adult individuals of different ages sampled longitudinally over a nine-year period. We observe a high inter-individual variability in the rates of change of cellular frequencies that correlate with baseline values, allowing identification of steady state levels towards which a cell subset converges and the ordered conver...
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
metadata only · no data-level QC for this typeStandardized, field-standard QC computed by touching the data — every metric states how it was obtained
No quantitative QC rubric exists for this data type yet, so it is deliberately left unscored — this is an honest "not applicable", not a poor rating.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently
Scientific quality
Based on hands-on reproduction of the papers that use this dataset. A reproducible paper that stands on this data is positive evidence; a flagged one is a prompt to look closer — never a verdict on the dataset itself without the evidence.