Integrating microarray-based spatial transcriptomics and single-cell RNA-seq reveals tissue architecture in pancreatic ductal adenocarcinomas
Single-cell RNA sequencing (scRNA-seq) enables the systematic identification of cell populations in a tissue, but characterizing their spatial organization remains challenging. We combine a microarray-based spatial transcriptomics method that reveals spatial patterns of gene expression using an array of spots, each capturing the transcriptomes of multiple adjacent cells, with scRNA-Seq generated from the same sample. To annotate the precise cellular composition of distinct tissue regions, we int...
Provenance — who produced it, who reused it
Linked to 24 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.
- SPOTlight: seeded NMF regression to deconvolute spatial transcri... 2021 · 753 cites
- Spatially informed cell-type deconvolution for spatial transcrip... 2022 · 516 cites
- Evaluation of cell-cell interaction methods by integrating singl... 2022 · 157 cites
- The Stress-Like Cancer Cell State Is a Consistent Component of T... 2020 · 114 cites
- A unified computational framework for single-cell data integrati... 2022 · 103 cites
- Coordinated single-cell tumor microenvironment dynamics reinforc... 2023 · 75 cites
18 further papers cite this accession but reuse could not be confirmed.
Deep data QC
87/100 · BStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
Human RNA-seq with 30 bp reads at 95.9% Q20 and 93.8% Q30 across 3.2 billion bases provides fixed-length sequences suitable for microRNA discovery or small-RNA profiling. The minimal N-content (0.001%) and 41.8% GC support reliable mapping to non-coding RNA databases; however, the short length restricts full-length transcript or isoform characterization.
The B 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
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.