GSE98479

Modeling gene regulation from matched expression and chromatin accessibility data

We propose a statistical method to model gene regulation by paired expression and chromatin accessibility (PECA) data, which dissects the regulatory elements (RE) of the genome by modeling their interaction with general chromatin regulators (CR) and sequence-specific transcriptional regulators (TF) and consequent effects on transcriptional changes.

Provenance — who produced it, who reused it

Linked to 2 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.

Standardized, 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