← BioTransfer GEO Dataset Finder
GEO series

Transcriptome Analysis in Human Breast Milk and Blood in a Randomized Trial after Inactivated or Attenuated Influenza Immunization

GSE281592 Homo sapiens (human) RNA-seq (gene expression) 69 samples Submitted 2025/05/13 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 69 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
69 samples: 20 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.
Summary (written by the submitters)
Transcriptomic signatures were identified in human peripheral blood mononuclear cells (PBMCs) and breast milk lymphocyte (BML) cells induced by trivalent inactivated influenza vaccine (TIV) or live attenuated influenza vaccine (LAIV) administered after delivery. We performed an RNA-Seq analysis on blood and breast milk samples from a subset of subjects enrolled in a randomized, double-blind controlled study in breastfeeding women who received either intranasal LAIV and intramuscular placebo, or intramuscular TIV and intranasal placebo (LAIV, n=10 and TIV, n=6).
Read the full summary ↓
Differentially expressed genes, gene clusters, and enriched pathways were identified. We observed increased innate immune signaling responses in BML but not in PBMC at Day 28 for the LAIV group. We hypothesize that breastfeeding extended the innate response to LAIV via mucosal immunity. An association between an increased IgG antibody response in TIV vs. LAIV identified in the parent study using ELISA corresponded to IGHG1 immunoglobulin gene expression in Day 28 PBMCs.
This dataset
Open GSE281592 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 GSE281592_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 PRJNA1184762. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
20 conditions, mostly in duplicate
Subject_E, trivalent inactivated influenza va… ×4 Subject_P, live attenuated influenza vaccine … ×4 Subject_A, live attenuated influenza vaccine … ×4 Subject_B, trivalent inactivated influenza va… ×4 Subject_L, live attenuated influenza vaccine … ×4 Subject_C, live attenuated influenza vaccine … ×4 Subject_J, trivalent inactivated influenza va… ×4 Subject_H, live attenuated influenza vaccine … ×3 +24 more

Supports a between-group comparison across 57 samples.

How we read this: 20 replicated groups read from 69 sample titles; they account for 57 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

+ 29 more — browse all 69 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.