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Cardiac Organoids for Modeling Hypertrophic Cardiomyopathy

GSE262876 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2025/01/28 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 16 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
16 samples: 16 samples, each with a distinct title — no replicated groupsGroups 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
MYBPC3 D389V Variant Induces Hypercontractility in Cardiac OrganoidsCells · 2024
Summary (written by the submitters)
BACKGROUND: MYBPC3 is one of the most mutated gene known to cause hypertrophic cardiomyopathy (HCM). However, the molecular mechanisms of how mutations in MYBPC3 lead to the onset and progression of HCM are poorly understood. Thus, advancing in-vitro studies to define these mechanisms of mutations leading to HCM are still warranted. Thus, the primary objective of this study was to investigate the molecular mechanisms underlying the pathogenesis of HCM associated with MYBPC3 mutation utilizing isogenic human-induced pluripotent stem cell (hiPSC)-derived cardiac organoids (hCOs).
Published in
MYBPC3 D389V Variant Induces Hypercontractility in Cardiac Organoids
Desai D, Song T, Singh RR et al. · Cells 2024 · PMID 39594661 · doi:10.3390/cells13221913
This dataset
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.

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 GSE262876_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1094569 and SRA study SRP498881. Searching any of these in the dataset finder brings you back here.

Study design
16 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 16 sample titles: 16 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
Datasets on a similar topic

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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.