Next generation sequencing of human immune cell subsets across diseases
This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the...
Provenance — who produced it, who reused it
Linked to 20 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.
- xCell: digitally portraying the tissue cellular heterogeneity la... 2017 · 4,663 cites
- Simultaneous enumeration of cancer and immune cell types from bu... 2017 · 1,440 cites
- A benchmark for RNA-seq deconvolution analysis under dynamic tes... 2021 · 177 cites
- Metacells untangle large and complex single-cell transcriptome n... 2022 · 86 cites
- Differential co-expression-based detection of conditional relati... 2019 · 81 cites
- Development of a fixed module repertoire for the analysis and in... 2021 · 76 cites
14 further papers cite this accession but reuse could not be confirmed.
Deep data QC
metadata only · no data-level QC for this typeStandardized, field-standard QC computed by touching the data — every metric states how it was obtained
No quantitative QC rubric exists for this data type yet, so it is deliberately left unscored — this is an honest "not applicable", not a poor rating.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently