Single-Cell Transcriptome Analysis of Lineage Diversity and Microenvironment in High-Grade Glioma
Despite extensive molecular characterization, we lack a comprehensive picture of lineage identity, differentiation, and microenvironmental composition in high-grade gliomas (HGGs). We sampled the cellular milieu of HGGs with massively-parallel single-cell RNA-Seq. While HGG cells can resemble glia or even immature neurons and form branched lineage structures, mesenchymal transformation results in unstructured populations. Glioma cells in a subset of mesenchymal tumors lose their neural lineage i...
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.
14 further papers cite this accession but reuse could not be confirmed.
Deep data QC
96/100 · AStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
Human RNA-seq with anomalously short 26 bp reads and severely elevated 1.492% N-content indicates technical issues during sequencing, possibly template degradation or optical defects. Although Q20 reached 93.3% and GC was 38.8%, the high N-fraction and short reads drastically reduce mapping confidence and isoform resolution; utility is limited to abundance-level quantification in well-annotated regions.
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
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.