Transcriptional profiling of SARS-CoV-2-infected Calu-3 cells.
RNA-seq (gene expression) · human · 42 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
- 42 samples: 42 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
- Redundant and distinct mechanisms suppress innate immune activation during SARS-CoV-2 infectionPLoS biology · 2026
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 GSE254699_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 PRJNA1071544 and SRA study SRP487104. 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 42 sample titles: 42 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.
- GSM8049049 Cmock-1__rep1
- GSM8049050 Cmock-2__rep2
- GSM8049051 Cmock-3__rep3
- GSM8049052 CVN1-1__rep1
- GSM8049053 CVN1-2__rep2
- GSM8049054 CVN1-3__rep3
- GSM8049055 CVN12M1-1__rep1
- GSM8049056 CVN12M1-2__rep2
- GSM8049057 CVN12M1-3__rep3
- GSM8049058 CVN13M-1__rep1
- GSM8049059 CVN13M-2__rep2
- GSM8049060 CVN13M-3__rep3
- GSM8049061 CVN14M-1__rep1
- GSM8049062 CVN14M-2__rep2
- GSM8049063 CVN14M-3__rep3
- GSM8049064 CVN15M-1__rep1
- GSM8049065 CVN15M-2__rep2
- GSM8049066 CVN15M-3__rep3
- GSM8049067 CVN16M-1__rep1
- GSM8049068 CVN16M-2__rep2
- GSM8049069 CVN16M-3__rep3
- GSM8049070 CVN2-1__rep1
- GSM8049071 CVN2-2__rep2
- GSM8049072 CVN2-3__rep3
- GSM8049073 CVN3M2-1__rep1
- GSM8049074 CVN3M2-2__rep2
- GSM8049075 CVN3M2-3__rep3
- GSM8049076 CVN6M1-1__rep1
- GSM8049077 CVN6M1-2__rep2
- GSM8049078 CVN6M1-3__rep3
- GSM8049079 CVO3M1-1__rep1
- GSM8049080 CVO3M1-2__rep2
- GSM8049081 CVO3M1-3__rep3
- GSM8049082 CVO6M1-1__rep1
- GSM8049083 CVO6M1-2__rep2
- GSM8049084 CVO6M1-3__rep3
- GSM8049085 CVO8M1-1__rep1
- GSM8049086 CVO8M1-2__rep2
- GSM8049087 CVO8M1-3__rep3
- GSM8049088 CVWT-1__rep1
+ 2 more — browse all 42 samples with per-sample file links →
- GSE201325 Whole transcriptome exploration revealed the dysregulated RNAs involved in SARS-CoV-2 spike protein inhibited apoptosis in Calu-3 cells 6 samples shares calu-3
- GSE167410 Histone H4 is increased in SARS-CoV-2-infected lung epithelial cells and linked to COVID-19 severity 16 samples shares sars-cov-2-infected
- GSE241292 SARS-CoV-2-infected human nasal epithelial air-liquid interface cultures 16 samples shares sars-cov-2-infected
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.