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RNA-sequencing of PBMC cultured with PolyI:C or LPS, from a pediatric cohort who received OM85 or placebo.

GSE184487 Homo sapiens (human) RNA-seq (gene expression) 193 samples Submitted 2024/09/20 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 193 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
193 samples: 10 conditions, mostly with about 16 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.
Summary (written by the submitters)
Bacterial-derived immune training agents are a showing promise in clinical studies for prevention of lower respiatory infections in high-risk infants but underlying mechanisms of this protective effect are unclear. To address this, we employed a systems-level analysis of transcriptional responses to immune stimuli (LPS and PolyI:C) in infants who participated in a clinical trial of one such agent called OM85 which was clinically effective.
Read the full summary ↓
We identified key protected innate immune changes using a series of analytical approaches such as reduced inflammatory responses to LPS and enhanced antibacterial interferon responses potentially mediated through IRF7. We posit that immune training agents exemplified by OM85 potentially protect against infant severe lower respiratory infection principally via effects on innate immune responses targeting the bacterial components of the mixed respiratory viral/bacterial infections which are characteristic of this age group.
This dataset
Open GSE184487 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 GSE184487_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 PRJNA764753 and SRA study SRP337969. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
10 conditions, mostly with about 16 replicates each
C, OM85 NT ×34 C, Placebo NT ×31 pre-treatment, unstimulated control, OM85 NT ×17 post-treatment, unstimulated control, OM85 NT ×17 post-treatment, LPS, OM85 NT ×16 pre-treatment, unstimulated control, Placebo … ×16 post-treatment, unstimulated control, Placeb… ×16 post-treatment, LPS, Placebo NT ×16 +2 more

Supports a between-group comparison across 193 samples.

How we read this: 10 replicated groups read from 193 sample titles; they account for 193 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

+ 153 more — browse all 193 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.