Characterizing the tumor microenvironment of metastatic ovarian cancer by single cell transcriptomics
Understanding the cellular composition of the tumor microenvironment and the interactions of the cells is essential to the development of successful immunotherapies in cancer. We perform single-cell RNA sequencing (scRNA-seq) of 9,885 cells isolated from the omentum in 6 patients with ovarian cancer and identify 9 major cell types, including cancer, stromal, and immune cells. Transcriptional analysis of immune cells stratifies our patient samples into 2 groups: (1) high T cell infiltration (high...
Provenance — who produced it, who reused it
Linked to 8 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.
7 further papers cite this accession but reuse could not be confirmed.
Deep data QC
100/100 · AStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
The A grade is a transparent weighted average. Each metric below scored from 0–100% against the published bulk-RNA-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