Inhibition of Salt-Inducible Kinases 2 and 3 reduces inflammatory signature in Psoriasis
Single-cell RNA-seq · human · 10 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Homo sapiens (human)
- Samples
- 10 samples: 10 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Read the full summary ↓
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE328285_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA1454483 and SRA study SRP692486. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 10 sample titles: 10 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM9677827 MUC20711_vehicle
- GSM9677829 MUC20712_GLPG3970
- GSM9677830 MUC20713_vehicle
- GSM9677831 MUC20714_GLPG3971
- GSM9677832 MUC20715_vehicle
- GSM9677833 MUC20716_GLPG3972
- GSM9677834 MUC20717_vehicle
- GSM9677835 MUC20718_GLPG3973
- GSM9677836 MUC20719_vehicle
- GSM9677837 MUC20720_GLPG3974
- GSE287022 Cutaneous adipose tissue has a strong inflammatory signature in psoriasis patients, and it is partly IL-17 dependent. 241 samples shares signature, psoriasis
- GSE316742 SGLT2 inhibition reverses metabolic and inflammatory kidney signatures in youth with type 1 diabetes 27 samples shares inhibition, signature
- GSE306800 Extracellular matrix-myCAF signatures correlate with resistance to neoadjuvant aPD-L1 immune checkpoint inhibition with durvalumab + metformin in HPV+ HNSCC 18 samples shares inhibition, signature
- GSE291471 Integrative blood profiling uncovers inflammatory network signatures in high-altitude pulmonary edema 83 samples shares signature
- GSE232127 Inflammatory signature of atopic dermatitis from tissue and systemic levels 75 samples shares signature
- GSE243625 Inflammatory transcriptomic signatures and cell type compositions in inflamed and non-inflamed colonic mucosa of ulcerative colitis 45 samples shares signature
- GSE254707 Single-cell transcriptomic analysis identifies infiltrating plasmacytoid dendritic cells in psoriasis epidermis 4988 samples shares psoriasis
- GSE286042 Transcriptomic and Proteomic Signatures Following AS03-adjuvanted Influenza A/H7N9 Vaccine 1232 samples shares signature
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.