Single-cell RNA-seq reveals AML hierarchies relevant to disease progression and immunity
Acute myeloid leukemia (AML) is a heterogeneous disease that resides within a complex microenvironment, complicating efforts to understand how different cell types contribute to disease progression. We combined single-cell RNA sequencing and genotyping to profile 38,410 cells from 40 bone marrow aspirates, including 16 AML patients and five healthy donors. We then applied a machine learning classifier to distinguish a spectrum of malignant cell types whose abundances varied between patients and...
Provenance — who produced it, who reused it
Linked to 34 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.
- Functional interpretation of single cell similarity maps 2019 · 285 cites
- Single-cell map of diverse immune phenotypes in the acute myeloi... 2021 · 137 cites
- Knowledge-primed neural networks enable biologically interpretab... 2020 · 135 cites
- Single-cell transcriptomic atlas-guided development of CAR-T cel... 2023 · 109 cites
- Single-cell analyses highlight the proinflammatory contribution... 2022 · 91 cites
28 further papers cite this accession but reuse could not be confirmed.
Deep data QC
19/100 · FStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
Human bulk-RNA-seq with 64 bp reads at only 76.3% Q20 and 63.8% Q30 represents poor sequencing quality, with mean base quality 28.6 indicating marginal basecall confidence. The 44.1% GC and 0% adapter contamination suggest an instrument or reagent issue rather than contamination; utility for expression analysis is questionable without substantial filtering and validation.
The F 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.