Identification and Targeting of Regulators of SARS-CoV-2-Host interactions in the Airway Epithelium
RNA-seq (gene expression) · human · 14 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 14 samples: 14 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
- Identification and targeting of regulators of SARS-CoV-2-host interactions in the airway epitheliumScience advances · 2025
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 GSE262588_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1092598 and SRA study SRP497402. 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 14 sample titles: 14 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.
- GSM8162955 MOCK, WVC1, scRNAseq
- GSM8162956 1dpi, WVC2, scRNAseq
- GSM8162957 3dpi, WVC3, scRNAseq
- GSM8162958 6dpi, WVC4, scRNAseq
- GSM8162959 Plate 1A, Untreated, DMSO, Drugs
- GSM8162960 Plate 1B, Untreated, DMSO, Drugs, Replicate Plate 1A
- GSM8162961 Plate 2A, Untreated, DMSO, Drugs
- GSM8162962 Plate 2B, Untreated, DMSO, Drugs, Replicate Plate 2A
- GSM8162963 Plate 4A, Untreated, DMSO, Drugs
- GSM8162964 Plate 4B, Untreated, DMSO, Drugs, Replicate Plate 4A
- GSM8162965 Plate 5A, Untreated, DMSO, Drugs
- GSM8162966 Plate 5B, Untreated, DMSO, Drugs, Replicate Plate 5A
- GSM8162967 Plate 6A, Untreated, DMSO, Drugs
- GSM8162968 Plate 6B, Untreated, DMSO, Drugs, Replicate Plate 6A
- GSE302095 Validation of bronchial airway gene expression associated with bronchiectasis in nasal epithelium 132 samples shares epithelium, airway
- GSE306517 Transcriptomic and functional responses of the cystic fibrosis airway epithelium to CFTR modulator therapy 76 samples shares epithelium, airway
- GSE272860 Hypoxia promotes airway differentiation in the human lung epithelium [Bulk RNA-seq] 18 samples shares epithelium, airway
- GSE235715 Multi-scaled transcriptomics of chronically inflamed nasal epithelium reveals immune-epithelial dynamics and tissue remodeling in nasal polyp formation 60 samples shares epithelium
- GSE293514 Development of a split-toxin CRISPR screening platform to systematically identify upstream regulators of human myoblast fusion 57 samples shares regulators
- GSE235714 Immune-Epithelial Interactions and Tissue Remodeling in the Inflammatory Respiratory Nasal Tract [NanoString GeoMx spatial transcriptomics] 40 samples shares interactions
- GSE226741 Expression changes of ecDNA in colorectal epithelium-adenoma-adenocarcinoma evolution 30 samples shares epithelium
- GSE333877 Epigenetic landscape, key transcriptional regulators, and in vivo identification of human Tr1 cells 72 samples shares regulators
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.