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Gene expression in patients with pulmonary hypertension due to valve heart disease

GSE325715 Homo sapiens (human) RNA-seq (gene expression) 146 samples Submitted 2026/03/26 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 146 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
146 samples: 115 × Blood, HTP_II, RNA-seq, S vs 30 × Blood, Control, RNA-seq, SGroups 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)
To delve deeper into the molecular mechanisms underlying pulmonary hypertension secondary to left heart disease (PH-LHD), an essential step toward developing a comprehensive classification, reliable biomarkers and targeted therapies. In this study, we analyzed the whole transcriptome (mRNA) of a unique cohort of patients with persistent PH due to valvular heart disease (PH-VHD) to identify biological pathways associated with disease prognosis.
Read the full summary ↓
The analysis was performed using the well-characterized SIOVAC (Sildenafil for Improving Outcomes after Valvular Correction) clinical trial cohort. We included 116 patients with demonstrated PH-LHD after valvular correction, and 30 VHD patients with no or mild PH (Control).
This dataset
Open GSE325715 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 GSE325715_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 PRJNA1441514 and SRA study SRP685974. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
115 × Blood, HTP_II, RNA-seq, S vs 30 × Blood, Control, RNA-seq, S

Supports a between-group comparison across 145 samples.

How we read this: 2 replicated groups read from 146 sample titles; they account for 145 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

+ 106 more — browse all 146 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.