← BioTransfer GEO Dataset Finder
GEO series

RNA-Sequencing Analysis of Type-I and Type-II Interferon Effects on an In-Vitro Human Thymic Epithelium Model

GSE281833 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2025/05/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 24 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
24 samples: 8 conditions, mostly in triplicateGroups 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)
The thymus plays a critical role in instructing T cell immunity and establishing central tolerance, yet its therapeutic potential remains largely unexplored. Understanding the signals that govern thymic epithelial cell differentiation is essential for advancing regenerative applications. Here, we investigate the pathways that influence thymic epithelial development by introducing human recombinant interferon-alpha (IFNA2) and interferon-gamma (IFNG) during the final stage of differentiation in an in-vitro human thymic epithelium model.
Read the full summary ↓
Using bulk RNA-sequencing, we examine signaling responses activated by interferons in the context of thymic development.
This dataset
Open GSE281833 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 GSE281833_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 PRJNA1185778 and SRA study SRP545073. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in triplicate
TEP Stage_No_IFN_Exp_1 ×3 TEP Stage_IFNA_Exp_1 ×3 TEP Stage_IFNG_Exp_1 ×3 TEP Stage_IFNA+G_Exp_1 ×3 TEP Stage_No_IFN_Exp_2 ×3 TEP Stage_IFNA_Exp_2 ×3 TEP Stage_IFNG_Exp_2 ×3 TEP Stage_IFNA+G_Exp_2 ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 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

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.