Single-cell RNA-seq reveals dynamic paracrine control of cellular variation
Here, we use a microfluidics-based approach to prepare single-cell RNA-Seq libraries from over 1,700 primary mouse dendritic cells (DCs) stimulated with three pathogenic components and examine variation between individual cells exposed to the same stimulus and general strategies that multicellular populations use to establish complex dynamic responses.
Provenance — who produced it, who reused it
Linked to 18 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.
- CEL-Seq2: sensitive highly-multiplexed single-cell RNA-Seq 2016 · 1,250 cites
- Efficient integration of heterogeneous single-cell transcriptome... 2019 · 997 cites
- Benchmarking algorithms for gene regulatory network inference fr... 2020 · 817 cites
- Cell lineage and communication network inference via optimizatio... 2019 · 166 cites
13 further papers cite this accession but reuse could not be confirmed.
Deep data QC
90/100 · 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