ATAC-seq data
The immune system depends on a balanced interplay among a variety of specialized cell types transitioning between resting and stimulated states. While epigenome mapping efforts have focused on resting ex vivo immune cells, efforts to characterize stimulation-induced chromatin changes of diverse cell types has been limited. Thus, we collected ATAC-seq and RNA-seq data from immune cell types under resting and stimulated conditions from blood of healthy individuals, and cell types from fetal thymus...
Provenance — who produced it, who reused it
Linked to 18 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.
- Landscape of stimulation-responsive chromatin across diverse hum... 2019 · 319 cites
- Identification of LZTFL1 as a candidate effector gene at a COVID... 2021 · 186 cites
- PeakVI: A deep generative model for single-cell chromatin access... 2022 · 107 cites
15 further papers cite this accession but reuse could not be confirmed.
Deep data QC
insufficient data to scoreStandardized, field-standard QC computed by touching the data — every metric states how it was obtained
The insufficient grade is a transparent weighted average. Each metric below scored from 0–100% against the published ATAC-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