A multi-omic single-cell atlas of human gynecological malignancies
Tumors show substantial amounts of cellular heterogeneity by forming complex ecosystems of malignant and non-malignant cells. Herein, we present a comprehensive multi-omic cell atlas of matched single-cell transcriptome and single-cell chromatin accessibility profiles spanning over 150,000 cells from 11 human gynecologic tumors. By jointly analyzing these transcriptomic and chromatin accessibility profiles at single-cell resolution, we identify 115,734 total peak-to-gene links representing putat...
Provenance — who produced it, who reused it
Linked to 21 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.
- A multi-omic single-cell landscape of human gynecologic malignan... 2021 · 136 cites
20 further papers cite this accession but reuse could not be confirmed.
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
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently