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RNA expression differences in innate immune response to COVID19 with advancing age.

GSE254647 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2024/03/27 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 36 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
36 samples: 10 conditions, mostly in duplicateGroups 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
Changes in the innate immune response to SARS-CoV-2 with advancing age in humansImmunity & ageing : I & A · 2024
Summary (written by the submitters)
We investigated differences in RNA expression between aged (65-90 years), middle-aged (41-63 years) and young (21-40 years) in response to COVID 19 to gain insight into the increased susceptibility of the elderly to the virus. To investigate this fresh PBMCs (1 x 106/ml) from the three age groups were stimulated for 24h with 5ug/ml of irradiated COVID19 virus- isolate USA-WA1/2020 obtained from Bei resources (NIAID).
Read the full summary ↓
Subsequently the cells were collected. Half of the collected cells were stored in DNA/RNA shield for RNA extraction. The rest were used for flow and other studies. Once all samples were collected, they were sent to UCI Genomics Research and Technology Hub, GRTH) for library preparation and sequencing.
Published in
Changes in the innate immune response to SARS-CoV-2 with advancing age in humans
Agrawal S, Tran MT, Jennings TSK et al. · Immunity & ageing : I & A 2024 · PMID 38515147 · doi:10.1186/s12979-024-00426-3
This dataset
Open GSE254647 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE254647_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA1071186 and SRA study SRP486949. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38515147) ↗
Study design
10 conditions, mostly in duplicate
PBMC Cells, Middle aged, Male, Unstim, ×5 PBMC Cells, Middle aged, Female, Covid stim, ×3 PBMC Cells, Middle aged, Male, Cov stim, ×2 PBMC Cells, Aged, Female, Unstim, ×2 PBMC Cells, Young, Male, Unstim, ×2 PBMC Cells, Young, Male, Cov stim, ×2 PBMC Cells, Middle aged, Male, Covid stim, ×2 PBMC Cells, Young, Female, Unstim, ×2 +14 more

Supports a between-group comparison across 24 samples.

How we read this: 10 replicated groups read from 36 sample titles; they account for 24 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.

Samples in this study
Datasets on a similar topic

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