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Differential Tropisms of Old and New World Hantaviruses Influence Virulence and Developing Host-Directed Antiviral Candidates

GSE232641 Homo sapiens (human) RNA-seq (gene expression) 68 samples Submitted 2024/05/16 Platform GPL24676Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 68 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
68 samples: 60 distinct titles, 4 of them repeatedGroups 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
Differential tropisms of old and new world hantaviruses influence virulence and developing host-directed antiviral candidatesPLoS pathogens · 2025
Summary (written by the submitters)
We report RNAseq analysis of control, calu3, astrocytes, cardiomyocytes and pulmonary endothelial cells under uninfected (mock) and Andes virus (ANDV), Sin Nombre virus (SNV), Hantaan virus (HTNV) infected and drug (synthetic 6AZA and Favipiravir, herbal Silymarin and Urolithin B) treated conditions
Published in
Differential tropisms of old and new world hantaviruses influence virulence and developing host-directed antiviral candidates
Jeyachandran AV, Irudayam JI, Dubey S et al. · PLoS pathogens 2025 · PMID 40857262 · doi:10.1371/journal.ppat.1013401
This dataset
Open GSE232641 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 GSE232641_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 PRJNA973079 and SRA study SRP438054. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40857262) ↗
Study design
60 distinct titles, 4 of them repeated
Pulmonary endothelial cells - Mock - 48hrs ×3 Pulmonary endothelial cells - Sin Nombre viru… ×3 Pulmonary endothelial cells - Andes virus - 4… ×3 Pulmonary endothelial cells - Hantaan virus -… ×3

How we read this: Read from 68 sample titles: 60 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.

Samples in this study

+ 28 more — browse all 68 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.