A single-cell and spatially resolved atlas of human breast cancers
This study presents a single cell and spatially resolved transcriptomics analysis of human breast cancers. We develop a single cell method of intrinsic subtype classification (scSubtype) to reveal recurrent neoplastic cell heterogeneity. Immunophenotyping using CITE-Seq provides high-resolution immune profiles, including novel PD-L1/PD-L2+ macrophage populations associated with clinical outcome. Mesenchymal cells displayed diverse functions and cell surface protein expression through differentia...
Provenance — who produced it, who reused it
Linked to 113 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.
- Cellular architecture of human brain metastases 2022 · 211 cites
- Identification of the novel exhausted T cell CD8 + markers in br... 2024 · 118 cites
- Current evidence and therapeutic implication of PANoptosis in ca... 2023 · 94 cites
- BIDCell: Biologically-informed self-supervised learning for segm... 2024 · 72 cites
76 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
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.