Distinct pulmonary and systemic effects of dexamethasone in severe COVID-19
Single-cell RNA-seq · human · 24 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
- 24 samples: 24 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.
- Paper
- Distinct pulmonary and systemic effects of dexamethasone in severe COVID-19Nature communications · 2024
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 GSE236030_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 PRJNA988459 and SRA study SRP446407. 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 24 sample titles: 24 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.
- GSM7517077 tracheal aspirate, Dex, patient 161, scRNAseq
- GSM7517078 tracheal aspirate, Dex, patient 340, scRNAseq
- GSM7517079 tracheal aspirate, Dex, patient 357, scRNAseq
- GSM7517080 tracheal aspirate, Dex, patient 389, scRNAseq
- GSM7517081 tracheal aspirate, Dex, patient 398, scRNAseq
- GSM7517082 tracheal aspirate, Dex, patient 403, scRNAseq
- GSM7517083 tracheal aspirate, Dex, patient 410, scRNAseq
- GSM7517084 tracheal aspirate, Dex, patient 414, scRNAseq
- GSM7517085 tracheal aspirate, Dex, patient 415, scRNAseq
- GSM7517086 tracheal aspirate, Dex, patient 471, scRNAseq
- GSM7517087 tracheal aspirate, NoDex, patient 1, scRNAseq
- GSM7517088 tracheal aspirate, NoDex, patient 107, scRNAseq
- GSM7517089 tracheal aspirate, NoDex, patient 2, scRNAseq
- GSM7517090 tracheal aspirate, NoDex, patient 24, scRNAseq
- GSM7517091 tracheal aspirate, NoDex, patient 50, scRNAseq
- GSM7517092 tracheal aspirate, NoDex, patient 72, scRNAseq
- GSM7517093 tracheal aspirate, NoDex, patient 89, scRNAseq
- GSM7517094 whole-blood, Dex, patient 402, scRNAseq
- GSM7517095 whole-blood, Dex, patient 403, scRNAseq
- GSM7517096 whole-blood, Dex, patient 405, scRNAseq
- GSM7517097 whole-blood, Dex, patient 412, scRNAseq
- GSM7517098 whole-blood, Dex, patient 414, scRNAseq
- GSM7517099 whole-blood, Dex, patient 415, scRNAseq
- GSM7517100 whole-blood, Dex, patient 427, scRNAseq
- GSE237180 Distinct pulmonary and systemic effects of dexamethasone in severe COVID-19. 45 samples shares covid-19, dexamethasone, pulmonary, distinct, systemic, severe
- GSE264443 Dynamic gene expression analysis reveals distinct severity phases of immune and cellular dysregulation in COVID-19 189 samples shares covid-19, distinct
- GSE202805 Global Transcriptomic analysis of PBMC derived from COVID-19 acute-severe patients and convalescents 80 samples shares covid-19, severe
- GSE152418 Systems biological assessment of immunity to severe and mild COVID-19 infections 34 samples shares covid-19, severe
- GSE212866 Dynamics of gene expression profiling by microarrays and identification of high-risk patients for severe COVID-19 230 samples shares covid-19, severe
- GSE320469 Identifying severe COVID-19 risk variants modulating enhancer reporter activity in lung cells 7 samples shares covid-19, severe
- GSE318645 Dual Immune Checkpoint Blockade Induces Distinct Systemic and Intratumoral Immune Activation in Recurrent Glioblastoma 226 samples shares distinct, systemic
- GSE303208 Single cell RNA seq of Healthy, covid-19 infected, recovered and long recovered individuals. 57 samples shares covid-19
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.