Single-cell analysis of lung epithelial cells reveals age and cell population-specific responses to SARS-CoV-2 infection in ciliated cells
Single-cell RNA-seq · human · 14 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- 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
- Single-cell analysis of lung epithelial cells reveals age and cell population-specific responses to SARS-CoV-2 infection in ciliated cellsClinical and experimental immunology · 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 GSE254266_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 PRJNA1069102 and SRA study SRP485970. Searching any of these in the dataset finder brings you back here.
Supports a case/control comparison: 7 samples read as cases, 7 as controls.
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.
- GSM8037017 lung, mock, donor1, pediatric, scRNAseq
- GSM8037018 lung, infected, donor1, pediatric, scRNAseq
- GSM8037019 lung, mock, donor2, pediatric, scRNAseq
- GSM8037020 lung, infected, donor2, pediatric, scRNAseq
- GSM8037021 lung, mock, donor3, pediatric, scRNAseq
- GSM8037022 lung, infected, donor3, pediatric, scRNAseq
- GSM8037023 lung, mock, donor4, pediatric, scRNAseq
- GSM8037024 lung, infected, donor4, pediatric, scRNAseq
- GSM8037025 lung, mock, donor5, pediatric, scRNAseq
- GSM8037026 lung, infected, donor5, pediatric, scRNAseq
- GSM8037027 lung, mock, donor6, adult, scRNAseq
- GSM8037028 lung, infected, donor6, adult, scRNAseq
- GSM8037029 lung, mock, donor7, adult, scRNAseq
- GSM8037030 lung, infected, donor7, adult, scRNAseq
- GSE243013 A single-cell atlas of immune heterogeneity in anti-PD1-treated non-small cell lung cancer 243 samples shares single-cell, lung
- GSE281740 single-cell RNA-sequence data of clinical small cell lung cancer samples 19 samples shares single-cell, lung
- GSE303324 SARS-CoV-2 Variant Boosters and Breakthrough Infections Drive Functional Differences in the Memory B Cell Repertoire 55 samples shares sars-cov-2
- GSE305971 Integrative single-cell analysis reveals malignant archetypes and proliferative hierarchies in multiple myeloma 2105 samples shares single-cell
- GSE328048 Single-cell transcriptome reveals keratinocyte subclusters that contribute to altered differentiation and inflammatory responses in atopic dermatitis 116 samples shares single-cell
- GSE263733 Single-cell transcriptome analysis reveals subtype-specific clonal evolution and microenvironmental changes in liver metastasis of pancreatic adenocarcinoma and their clinical implications 218 samples shares single-cell
- GSE282122 A longitudinal single-cell atlas of anti-tumour necrosis factor treatment in inflammatory bowel disease 216 samples shares single-cell
- GSE303346 Single-Cell RNA-Seq Reveals Immunosuppressive Effects of Triple-Negative Breast Cancer–Derived Exosomes on NK Cell Responses 16 samples shares single-cell
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.