Development of an ideal inactivated vaccine for COVID-19 (mouse lung RNA-seq data)
RNA-seq (gene expression) · mouse · 52 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
- Mus musculus (mouse)
- Samples
- 52 samples: 11 conditions, mostly with about 5 replicates eachGroups 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 GSE270151_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 PRJNA1125346 and SRA study SRP514653. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 52 samples.
How we read this: 11 replicated groups read from 52 sample titles; they account for 52 of them. 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.
- GSM8335592 unvaccinated, 3dpi, rep1 unvaccinated, 3dpi,
- GSM8335593 unvaccinated, 3dpi, rep2 unvaccinated, 3dpi,
- GSM8335594 unvaccinated, 3dpi, rep3 unvaccinated, 3dpi,
- GSM8335595 unvaccinated, 3dpi, rep4 unvaccinated, 3dpi,
- GSM8335596 FC-WPV_1μg, 3dpi, rep1 FC-WPV_1μg, 3dpi,
- GSM8335597 FC-WPV_1μg, 3dpi, rep2 FC-WPV_1μg, 3dpi,
- GSM8335598 FC-WPV_1μg, 3dpi, rep3 FC-WPV_1μg, 3dpi,
- GSM8335599 FC-WPV_1μg, 3dpi, rep4 FC-WPV_1μg, 3dpi,
- GSM8335600 FC-WPV_1μg, 3dpi, rep5 FC-WPV_1μg, 3dpi,
- GSM8335601 FC-WPV_5μg, 3dpi, rep1 FC-WPV_5μg, 3dpi,
- GSM8335602 FC-WPV_5μg, 3dpi, rep2 FC-WPV_5μg, 3dpi,
- GSM8335603 FC-WPV_5μg, 3dpi, rep3 FC-WPV_5μg, 3dpi,
- GSM8335604 FC-WPV_5μg, 3dpi, rep4 FC-WPV_5μg, 3dpi,
- GSM8335605 FC-WPV_5μg, 3dpi, rep5 FC-WPV_5μg, 3dpi,
- GSM8335606 CF-WPV_1μg, 3dpi, rep1 CF-WPV_1μg, 3dpi,
- GSM8335607 CF-WPV_1μg, 3dpi, rep2 CF-WPV_1μg, 3dpi,
- GSM8335608 CF-WPV_1μg, 3dpi, rep3 CF-WPV_1μg, 3dpi,
- GSM8335609 CF-WPV_1μg, 3dpi, rep4 CF-WPV_1μg, 3dpi,
- GSM8335610 CF-WPV_1μg, 3dpi, rep5 CF-WPV_1μg, 3dpi,
- GSM8335611 CF-WPV_5μg, 3dpi, rep1 CF-WPV_5μg, 3dpi,
- GSM8335612 CF-WPV_5μg, 3dpi, rep2 CF-WPV_5μg, 3dpi,
- GSM8335613 CF-WPV_5μg, 3dpi, rep3 CF-WPV_5μg, 3dpi,
- GSM8335614 CF-WPV_5μg, 3dpi, rep4 CF-WPV_5μg, 3dpi,
- GSM8335615 CF-WPV_5μg, 3dpi, rep5 CF-WPV_5μg, 3dpi,
- GSM8335616 unvaccinated, 10dpi, rep1 unvaccinated, 10dpi,
- GSM8335617 unvaccinated, 10dpi, rep2 unvaccinated, 10dpi,
- GSM8335618 unvaccinated, 10dpi, rep3 unvaccinated, 10dpi,
- GSM8335619 unvaccinated, 10dpi, rep4 unvaccinated, 10dpi,
- GSM8335620 FC-WPV_1μg, 10dpi, rep1 FC-WPV_1μg, 10dpi,
- GSM8335621 FC-WPV_1μg, 10dpi, rep2 FC-WPV_1μg, 10dpi,
- GSM8335622 FC-WPV_1μg, 10dpi, rep3 FC-WPV_1μg, 10dpi,
- GSM8335623 FC-WPV_1μg, 10dpi, rep4 FC-WPV_1μg, 10dpi,
- GSM8335624 FC-WPV_1μg, 10dpi, rep5 FC-WPV_1μg, 10dpi,
- GSM8335625 FC-WPV_5μg, 10dpi, rep1 FC-WPV_5μg, 10dpi,
- GSM8335626 FC-WPV_5μg, 10dpi, rep2 FC-WPV_5μg, 10dpi,
- GSM8335627 FC-WPV_5μg, 10dpi, rep3 FC-WPV_5μg, 10dpi,
- GSM8335628 FC-WPV_5μg, 10dpi, rep4 FC-WPV_5μg, 10dpi,
- GSM8335629 FC-WPV_5μg, 10dpi, rep5 FC-WPV_5μg, 10dpi,
- GSM8335630 CF-WPV_1μg, 10dpi, rep1 CF-WPV_1μg, 10dpi,
- GSM8335631 CF-WPV_1μg, 10dpi, rep2 CF-WPV_1μg, 10dpi,
+ 12 more — browse all 52 samples with per-sample file links →
- GSE300288 Single-cell and spatial transcriptomics analysis of tobacco-associated lung adenocarcinoma development, and in response to targeting inflammation alone or in combination with immune checkpoint blockade in precancerous phase [scRNA-seq] 31 samples shares rna-seq, lung
- GSE226609 Mouse lung tissue RNA-Seq from C57Bl6 wild type and ALOX15 KO mice with and without house dust mite (HDM) exposure. 20 samples shares rna-seq, lung
- GSE306230 RNA-seq of mouse lung tissue after irradiation 12 samples shares rna-seq, lung
- GSE264278 TIme-cource single-cell RNA-seq analysis of bleomycin and LPS-induced lung injury and fibrosis 18 samples shares rna-seq, lung
- GSE297298 Single-cell RNA-sequencing identifies anti-cancer immune phenotypes in the early lung metastatic niche during breast cancer 18 samples shares rna-seq, lung
- GSE331228 RNA-seq profiling of liver and lung of CLP mice(6h) 12 samples shares rna-seq, lung
- GSE326100 scRNA-seq of mouse cochlea organoid cells 768 samples shares rna-seq
- GSE311449 Single cell RNA-seq of mouse brain vascular cells with Smart-seq2 method 391 samples shares rna-seq
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.