Single cell RNA-seq of primary human glioblastomas
We report transcriptomes from 430 single glioblastoma cells isolated from 5 individual tumors and 102 single cells from gliomasphere cells lines generated using SMART-seq. In addition, we report population RNA-seq from the five tumors as well as RNA-seq from cell lines derived from 3 tumors (MGH26, MGH28, MGH31) cultured under serum free (GSC) and differentiated (DGC) conditions. This dataset highlights intratumoral heterogeneity with regards to the expression of de novo derived transcriptional...
Provenance — who produced it, who reused it
Linked to 23 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.
- A general and flexible method for signal extraction from single-... 2018 · 837 cites
- Linking transcriptional and genetic tumor heterogeneity through... 2018 · 265 cites
- The linker histone H1.0 generates epigenetic and functional intr... 2016 · 201 cites
- Quantification of cell identity from single-cell gene expression... 2015 · 170 cites
- Chromatin landscapes reveal developmentally encoded transcriptio... 2019 · 142 cites
- Linnorm: improved statistical analysis for single cell RNA-seq e... 2017 · 134 cites
- Detecting heterogeneity in single-cell RNA-Seq data by non-negat... 2017 · 97 cites
- Using single nucleotide variations in single-cell RNA-seq to ide... 2018 · 88 cites
- Glioblastoma cell populations with distinct oncogenic programs r... 2021 · 78 cites
13 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
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