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Integrated Transcriptomic and Immune Analysis Reveals Distinct Mitochondrial and Immune Signature in COVID-19 ARDS Requiring Invasive Mechanical Ventilation

GSE336577 Homo sapiens (human) RNA-seq (gene expression) 94 samples Submitted 2026/07/29 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 94 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
94 samples: 26 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.
Paper
Integrated transcriptomic and immune analysis reveals distinct mitochondrial and immune signature in COVID-19 ARDS requiring invasive mechanical ventilationFrontiers in medicine · 2026
Summary (written by the submitters)
Patients requiring Invasive Mechanical Ventilation (IMV) compared to patients who are non-Invasive Mechanical Ventilation (non-IMV)demonstrated distinct transcriptomic and immune profiles associated with severe COVID-19. These findings identify candidate biomarkers and pathways associated with disease severity; however, the results are exploratory and require validation in larger cohorts and functional studies.
Published in
Integrated transcriptomic and immune analysis reveals distinct mitochondrial and immune signature in COVID-19 ARDS requiring invasive mechanical ventilation
Gotur DB, Gowda DM, Pinkaew D et al. · Frontiers in medicine 2026 · PMID 42487974 · doi:10.3389/fmed.2026.1856132
This dataset
Open GSE336577 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 GSE336577_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 PRJNA1482000 and SRA study SRP712563. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42487974) ↗
Study design
26 conditions, mostly in duplicate
1002_IMV_D ×2 1003_non-IMV_D ×2 1006_non-IMV_D ×2 1008_non-IMV_D ×2 1009_non-IMV_D ×2 1010_IMV_D ×2 1011_non-IMV_D ×2 1012_IMV_D ×2 +60 more

Supports a between-group comparison across 52 samples.

How we read this: 26 replicated groups read from 94 sample titles; they account for 52 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

+ 54 more — browse all 94 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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