The dynamic transcriptional landscape of mammalian organogenesis at single cell resolution
During mammalian organogenesis, the cells of the three germ layers transform into an embryo that includes most major internal and external organs. The key regulators of developmental defects can be studied during this crucial period, but conventional approaches lack the throughput and resolution to obtain a global view of the molecular states and trajectories of a rapidly diversifying and expanding number of cell types. Here we set out to investigate the transcriptional dynamics of mouse develop...
Provenance — who produced it, who reused it
Linked to 15 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.
- Analytic Pearson residuals for normalization of single-cell RNA-... 2021 · 206 cites
- Spatially exploring RNA biology in archival formalin-fixed paraf... 2024 · 87 cites
- Somatic mutations and single-cell transcriptomes reveal the root... 2021 · 84 cites
- Comparison of visualization tools for single-cell RNAseq data 2020 · 82 cites
- BIDCell: Biologically-informed self-supervised learning for segm... 2024 · 72 cites
9 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