Single-Cell mRNA Sequencing Reveals Rare Intestinal Cell Types
Understanding the development and function of an organ requires the characterization of all of its cell types. Traditional methods for visualizing and isolating sub-populations of cells are based on mRNA or protein expression of only few known marker genes. The unequivocal identification of a specific marker gene, however, poses a major challenge, particularly if this cell type is rare. Identifying rare cell types, such as stem cells, short-lived progenitors, cancer stem cells, or circulating tu...
Provenance — who produced it, who reused it
Linked to 5 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.
- Exploiting single-cell expression to characterize co-expression... 2016 · 94 cites
- GiniClust2: a cluster-aware, weighted ensemble clustering method... 2018 · 89 cites
3 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